For many multicellular organisms, a microscopic study shows that microbial cells
outnumber host cells by perhaps ten to one. Until recently, these abundant
communities of host-associated microbes were largely unstudied, often for lack
of analytical tools or conceptual frameworks. The advent of new tools is rendering
visible this previously ignored biosphere and the results have been startling.
Many facets of host biology have proven to be profoundly affected by the
associated microbiomes. As a result, several large-scale projects — such as
the
Human Microbiome Project
— have been undertaken to jump start an understanding
of this critical component of the biosphere.

Created with PubMed® Query:
"microbiome project" NOT pmcbook NOT ispreviousversion

Many colobine species-including the endangered Guizhou snub-nosed monkey (Rhinopithecus brelichi) are difficult to maintain in captivity and frequently exhibit gastrointestinal (GI) problems. GI problems are commonly linked to alterations in the gut microbiota, which lead us to examine the gut microbial communities of wild and captive R. brelichi. We used high-throughput sequencing of the 16S rRNA gene to compare the gut microbiota of wild (N = 7) and captive (N = 8) R. brelichi. Wild monkeys exhibited increased gut microbial diversity based on the Chao1 but not Shannon diversity metric and greater relative abundances of bacteria in the Lachnospiraceae and Ruminococcaceae families. Microbes in these families digest complex plant materials and produce butyrate, a short chain fatty acid critical to colonocyte health. Captive monkeys had greater relative abundances of Prevotella and Bacteroides species, which degrade simple sugars and carbohydrates, like those present in fruits and cornmeal, two staples of the captive R. brelichi diet. Captive monkeys also had a greater abundance of Akkermansia species, a microbe that can thrive in the face of host malnutrition. Taken together, these findings suggest that poor health in captive R. brelichi may be linked to diet and an altered gut microbiota.

Now is an opportune time to foster collaborations across sectors and geographical boundaries to enable development of best practices for drinking water (DW) microbiome research, focusing on accuracy and reproducibility of meta-omic techniques (while learning from past microbiome projects). A large-scale coordinated effort that builds on this foundation will enable the urgently needed comprehensive spatiotemporal understanding and control of DW microbiomes by engineering interventions to protect public health. This opinion paper highlights the need to initiate and conduct a large-scale coordinated DW microbiome project by addressing key knowledge gaps and recommends a roadmap for this effort.

@article {pmid31031092,
year = {2019},
author = {Hull, NM and Ling, F and Pinto, AJ and Albertsen, M and Jang, HG and Hong, PY and Konstantinidis, KT and LeChevallier, M and Colwell, RR and Liu, WT},
title = {Drinking Water Microbiome Project: Is it Time?.},
journal = {Trends in microbiology},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.tim.2019.03.011},
pmid = {31031092},
issn = {1878-4380},
abstract = {Now is an opportune time to foster collaborations across sectors and geographical boundaries to enable development of best practices for drinking water (DW) microbiome research, focusing on accuracy and reproducibility of meta-omic techniques (while learning from past microbiome projects). A large-scale coordinated effort that builds on this foundation will enable the urgently needed comprehensive spatiotemporal understanding and control of DW microbiomes by engineering interventions to protect public health. This opinion paper highlights the need to initiate and conduct a large-scale coordinated DW microbiome project by addressing key knowledge gaps and recommends a roadmap for this effort.},
}

Correct identification of different human epithelial materials such as from skin, saliva and vaginal origin is relevant in forensic casework as it provides crucial information for crime reconstruction. However, the overlap in human cell type composition between these three epithelial materials provides challenges for their differentiation and identification when using previously proposed human cell biomarkers, while their microbiota composition largely differs. By using validated 16S rRNA gene massively parallel sequencing data from the Human Microbiome Project of 1636 skin, oral and vaginal samples, 50 taxonomy-independent deep learning networks were trained to classify these three tissues. Validation testing was performed in de-novo generated high-throughput 16S rRNA gene sequencing data using the Ion Torrent™ Personal Genome Machine from 110 test samples: 56 hand skin, 31 saliva and 23 vaginal secretion specimens. Body-site classification accuracy of these test samples was very high as indicated by AUC values of 0.99 for skin, 0.99 for oral, and 1 for vaginal secretion. Misclassifications were limited to 3 (5%) skin samples. Additional forensic validation testing was performed in mock casework samples by de-novo high-throughput sequencing of 19 freshly-prepared samples and 22 samples aged for 1 up to 7.6 years. All of the 19 fresh and 20 (91%) of the 22 aged mock casework samples were correctly tissue-type classified. Moreover, comparing the microbiome results with outcomes from previous human mRNA-based tissue identification testing in the same 16 aged mock casework samples reveals that our microbiome approach performs better in 12 (75%), similarly in 2 (12.5%), and less good in 2 (12.5%) of the samples. Our results demonstrate that this new microbiome approach allows for accurate tissue-type classification of three human epithelial materials of skin, oral and vaginal origin, which is highly relevant for future forensic investigations.

The mammalian order primates contains wide species diversity. Members of the subfamily Colobinae are unique amongst extant primates in that their gastrointestinal systems more closely resemble those of ruminants than other members of the primate order. In the growing literature surrounding nonhuman primate microbiomes, analysis of microbial communities has been limited to the hindgut, since few studies have captured data on other gut sites, including the foregut of colobine primates. In this study, we used the red-shanked douc (Pygathrix nemaeus) as a model for colobine primates to study the relationship between gastrointestinal bacterial community structure and gut site within and between subjects. We analyzed fecal and pregastric stomach content samples, representative of the hindgut and foregut respectively, using 16S recombinant DNA (rDNA) sequencing and identified microbiota using closed-reference operational taxonomic unit (OTU) picking against the GreenGenes database. Our results show divergent bacterial communities clearly distinguish the foregut and hindgut microbiomes. We found higher bacterial biodiversity and a higher Firmicutes:Bacteroides ratio in the hindgut as opposed to the foregut. These gut sites showed strong associations with bacterial function. Specifically, energy metabolism was upregulated in the hindgut, whereas detoxification was increased in the foregut. Our results suggest a red-shanked douc's foregut microbiome is no more concordant with its own hindgut than it is with any other red-shanked douc's hindgut microbiome, thus reinforcing the notion that the bacterial communities of the foregut and hindgut are distinctly unique.

@article {pmid30997937,
year = {2019},
author = {Clayton, JB and Shields-Cutler, RR and Hoops, SL and Al-Ghalith, GA and Sha, JCM and Johnson, TJ and Knights, D},
title = {Bacterial community structure and function distinguish gut sites in captive red-shanked doucs (Pygathrix nemaeus).},
journal = {American journal of primatology},
volume = {},
number = {},
pages = {e22977},
doi = {10.1002/ajp.22977},
pmid = {30997937},
issn = {1098-2345},
support = {T32 DA007097-32//National Institute on Drug Abuse/ ; //Margot Marsh Biodiversity Foundation/ ; T32 DA007097-32//PharmacoNeuroImmunology Fellowship/ ; },
abstract = {The mammalian order primates contains wide species diversity. Members of the subfamily Colobinae are unique amongst extant primates in that their gastrointestinal systems more closely resemble those of ruminants than other members of the primate order. In the growing literature surrounding nonhuman primate microbiomes, analysis of microbial communities has been limited to the hindgut, since few studies have captured data on other gut sites, including the foregut of colobine primates. In this study, we used the red-shanked douc (Pygathrix nemaeus) as a model for colobine primates to study the relationship between gastrointestinal bacterial community structure and gut site within and between subjects. We analyzed fecal and pregastric stomach content samples, representative of the hindgut and foregut respectively, using 16S recombinant DNA (rDNA) sequencing and identified microbiota using closed-reference operational taxonomic unit (OTU) picking against the GreenGenes database. Our results show divergent bacterial communities clearly distinguish the foregut and hindgut microbiomes. We found higher bacterial biodiversity and a higher Firmicutes:Bacteroides ratio in the hindgut as opposed to the foregut. These gut sites showed strong associations with bacterial function. Specifically, energy metabolism was upregulated in the hindgut, whereas detoxification was increased in the foregut. Our results suggest a red-shanked douc's foregut microbiome is no more concordant with its own hindgut than it is with any other red-shanked douc's hindgut microbiome, thus reinforcing the notion that the bacterial communities of the foregut and hindgut are distinctly unique.},
}

RevDate: 2019-04-14

Parida S, D Sharma (2019)

The power of small changes: Comprehensive analyses of microbial dysbiosis in breast cancer.

Disparate occurrence of breast cancer remains an intriguing question since only a subset of women with known risk factors develop cancer. Recent studies suggest an active role of local and distant microbiota in breast cancer initiation, progression, and overall prognosis. A dysbiotic microbiota predisposes the body to develop cancer by inducing genetic instability, initiating DNA damage and proliferation of the damaged progeny, eliciting favorable immune response, metabolic dysregulation and altered response to therapy. In this review, we present our analyses of the existing datasets and discuss the local dysbiosis observed in breast cancer patients and different aspects of breast carcinogenesis that can be potentially influenced by local breast microbiota. Striking differences between microbial community compositions in breast of cancer patients compared to healthy individuals were noted. Differences in microbiome were also apparent between benign and malignant disease and between nipple aspirate fluid of healthy individuals and breast survivors. We also discuss the identification of distinct bacterial, fungal, viral as well as parasite signatures for breast cancer. These microbes are capable of producing numerous secondary metabolites that can act as signaling mediators effecting breast cancer progression. We review how microbes potentially alter response to therapy affecting drug metabolism, pharmacokinetics, anti-tumor effects and toxicity. In conclusion, breast harbors a community of microbes that can communicate with the host cells inducing downstream signaling pathways and modulating various aspects of breast cancer growth and metastatic progression and an improved understanding of microbial dysbiosis can potentially reduce breast cancer risk and improve outcomes of breast cancer patients. The human microbiome, now referred to as, the "forgotten organ" contains a metagenome that is 100-fold more diverse compared to the human genome, thereby, is critically associated with human health [1,2]. With the revelations of the human microbiome project and advent of deep sequencing techniques, a plethora of information has been acquired in recent years. Body sites like stomach, bladder and lungs, once thought to be sterile, are now known to harbor millions of indigenous microbial species. Approximately 80% of the healthy microbiome consists of Firmicutes and Bacteroidetes accompanied by Verrucomicrobia, Actinobacteria, Proteobacteria, Tenericutes and Cyanobacteria [2-7]. The role of microbiome in diabetes, obesity and even neurodegenerative diseases was greatly appreciated in the last decade [1,7-14] and now it has been established that microbiome significantly contributes to many organ specific cancers [1,15,16].

@article {pmid30981803,
year = {2019},
author = {Parida, S and Sharma, D},
title = {The power of small changes: Comprehensive analyses of microbial dysbiosis in breast cancer.},
journal = {Biochimica et biophysica acta. Reviews on cancer},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.bbcan.2019.04.001},
pmid = {30981803},
issn = {1879-2561},
abstract = {Disparate occurrence of breast cancer remains an intriguing question since only a subset of women with known risk factors develop cancer. Recent studies suggest an active role of local and distant microbiota in breast cancer initiation, progression, and overall prognosis. A dysbiotic microbiota predisposes the body to develop cancer by inducing genetic instability, initiating DNA damage and proliferation of the damaged progeny, eliciting favorable immune response, metabolic dysregulation and altered response to therapy. In this review, we present our analyses of the existing datasets and discuss the local dysbiosis observed in breast cancer patients and different aspects of breast carcinogenesis that can be potentially influenced by local breast microbiota. Striking differences between microbial community compositions in breast of cancer patients compared to healthy individuals were noted. Differences in microbiome were also apparent between benign and malignant disease and between nipple aspirate fluid of healthy individuals and breast survivors. We also discuss the identification of distinct bacterial, fungal, viral as well as parasite signatures for breast cancer. These microbes are capable of producing numerous secondary metabolites that can act as signaling mediators effecting breast cancer progression. We review how microbes potentially alter response to therapy affecting drug metabolism, pharmacokinetics, anti-tumor effects and toxicity. In conclusion, breast harbors a community of microbes that can communicate with the host cells inducing downstream signaling pathways and modulating various aspects of breast cancer growth and metastatic progression and an improved understanding of microbial dysbiosis can potentially reduce breast cancer risk and improve outcomes of breast cancer patients. The human microbiome, now referred to as, the "forgotten organ" contains a metagenome that is 100-fold more diverse compared to the human genome, thereby, is critically associated with human health [1,2]. With the revelations of the human microbiome project and advent of deep sequencing techniques, a plethora of information has been acquired in recent years. Body sites like stomach, bladder and lungs, once thought to be sterile, are now known to harbor millions of indigenous microbial species. Approximately 80% of the healthy microbiome consists of Firmicutes and Bacteroidetes accompanied by Verrucomicrobia, Actinobacteria, Proteobacteria, Tenericutes and Cyanobacteria [2-7]. The role of microbiome in diabetes, obesity and even neurodegenerative diseases was greatly appreciated in the last decade [1,7-14] and now it has been established that microbiome significantly contributes to many organ specific cancers [1,15,16].},
}

Horizontal gene transfer (HGT) is widespread in the evolution of prokaryotes, especially those associated with the human body. Here, we implemented large-scale gene-species phylogenetic tree reconstructions and reconciliations to identify putative HGT-derived genes in the reference genomes of microbiota isolated from six major human body sites by the NIH Human Microbiome Project. Comparisons with a control group representing microbial genomes from diverse natural environments indicated that HGT activity increased significantly in the genomes of human microbiota, which is confirmatory of previous findings. Roughly, more than half of total genes in the genomes of human-associated microbiota were transferred (donated or received) by HGT. Up to 60% of the detected HGTs occurred either prior to the colonization of the human body or involved bacteria residing in different body sites. The latter could suggest 'genetic crosstalk' and movement of bacterial genes within the human body via hitherto poorly understood mechanisms. We also observed that HGT activity increased significantly among closely-related microorganisms and especially when they were united by physical proximity, suggesting that the 'phylogenetic effect' can significantly boost HGT activity. Finally, we identified several core and widespread genes least influenced by HGT that could become useful markers for building robust 'trees of life' and address several outstanding technical challenges to improve the phylogeny-based genome-wide HGT detection method for future applications.

@article {pmid30976019,
year = {2019},
author = {Jeong, H and Arif, B and Caetano-Anollés, G and Kim, KM and Nasir, A},
title = {Horizontal gene transfer in human-associated microorganisms inferred by phylogenetic reconstruction and reconciliation.},
journal = {Scientific reports},
volume = {9},
number = {1},
pages = {5953},
doi = {10.1038/s41598-019-42227-5},
pmid = {30976019},
issn = {2045-2322},
support = {20140428//Ministry of Oceans and Fisheries (MOF)/ ; 21 519/SRGP/R&D/HEC/2014//Higher Education Commission, Pakistan (HEC)/ ; },
abstract = {Horizontal gene transfer (HGT) is widespread in the evolution of prokaryotes, especially those associated with the human body. Here, we implemented large-scale gene-species phylogenetic tree reconstructions and reconciliations to identify putative HGT-derived genes in the reference genomes of microbiota isolated from six major human body sites by the NIH Human Microbiome Project. Comparisons with a control group representing microbial genomes from diverse natural environments indicated that HGT activity increased significantly in the genomes of human microbiota, which is confirmatory of previous findings. Roughly, more than half of total genes in the genomes of human-associated microbiota were transferred (donated or received) by HGT. Up to 60% of the detected HGTs occurred either prior to the colonization of the human body or involved bacteria residing in different body sites. The latter could suggest 'genetic crosstalk' and movement of bacterial genes within the human body via hitherto poorly understood mechanisms. We also observed that HGT activity increased significantly among closely-related microorganisms and especially when they were united by physical proximity, suggesting that the 'phylogenetic effect' can significantly boost HGT activity. Finally, we identified several core and widespread genes least influenced by HGT that could become useful markers for building robust 'trees of life' and address several outstanding technical challenges to improve the phylogeny-based genome-wide HGT detection method for future applications.},
}

RevDate: 2019-04-11

Pinto D, Sorbellini E, Marzani B, et al (2019)

Scalp bacterial shift in Alopecia areata.

PloS one, 14(4):e0215206 pii:PONE-D-18-20093.

The role of microbial dysbiosis in scalp disease has been recently hypothesized. However, little information is available with regards to the association between microbial population on the scalp and hair diseases related to hair growth. Here we investigated bacterial communities in healthy and Alopecia areata (AA) subjects. The analysis of bacterial distribution at the genus level highlighted an increase of Propionibacterium in AA subjects alongside a general decrease of Staphylococcus. Analysis of log Relative abundance of main bacterial species inhabiting the scalp showed a significant increase of Propionibacterium acnes in AA subjects compared to control ones. AA scalp condition is also associated with a significant decrease of Staphylococcus epidermidis relative abundance. No significant changes were found for Staphylococcus aureus. Therefore, data from sequencing profiling of the bacterial population strongly support a different microbial composition of the different area surrounded hair follicle from the epidermis to hypodermis, highlighting differences between normal and AA affected the scalp. Our results highlight, for the first time, the presence of a microbial shift on the scalp of patients suffering from AA and gives the basis for a larger and more complete study of microbial population involvement in hair disorders.

@article {pmid30973913,
year = {2019},
author = {Pinto, D and Sorbellini, E and Marzani, B and Rucco, M and Giuliani, G and Rinaldi, F},
title = {Scalp bacterial shift in Alopecia areata.},
journal = {PloS one},
volume = {14},
number = {4},
pages = {e0215206},
doi = {10.1371/journal.pone.0215206},
pmid = {30973913},
issn = {1932-6203},
abstract = {The role of microbial dysbiosis in scalp disease has been recently hypothesized. However, little information is available with regards to the association between microbial population on the scalp and hair diseases related to hair growth. Here we investigated bacterial communities in healthy and Alopecia areata (AA) subjects. The analysis of bacterial distribution at the genus level highlighted an increase of Propionibacterium in AA subjects alongside a general decrease of Staphylococcus. Analysis of log Relative abundance of main bacterial species inhabiting the scalp showed a significant increase of Propionibacterium acnes in AA subjects compared to control ones. AA scalp condition is also associated with a significant decrease of Staphylococcus epidermidis relative abundance. No significant changes were found for Staphylococcus aureus. Therefore, data from sequencing profiling of the bacterial population strongly support a different microbial composition of the different area surrounded hair follicle from the epidermis to hypodermis, highlighting differences between normal and AA affected the scalp. Our results highlight, for the first time, the presence of a microbial shift on the scalp of patients suffering from AA and gives the basis for a larger and more complete study of microbial population involvement in hair disorders.},
}

BACKGROUND: Current methods used for annotating metagenomics shotgun sequencing (MGS) data rely on a computationally intensive and low-stringency approach of mapping each read to a generic database of proteins or reference microbial genomes.

RESULTS: We developed MGS-Fast, an analysis approach for shotgun whole-genome metagenomic data utilizing Bowtie2 DNA-DNA alignment of reads that is an alternative to using the integrated catalog of reference genes database of well-annotated genes compiled from human microbiome data. This method is rapid and provides high-stringency matches (>90% DNA sequence identity) of the metagenomics reads to genes with annotated functions. We demonstrate the use of this method with data from a study of liver disease and synthetic reads, and Human Microbiome Project shotgun data, to detect differentially abundant Kyoto Encyclopedia of Genes and Genomes gene functions in these experiments. This rapid annotation method is freely available as a Galaxy workflow within a Docker image.

RESULTS: We developed MGS-Fast, an analysis approach for shotgun whole-genome metagenomic data utilizing Bowtie2 DNA-DNA alignment of reads that is an alternative to using the integrated catalog of reference genes database of well-annotated genes compiled from human microbiome data. This method is rapid and provides high-stringency matches (>90% DNA sequence identity) of the metagenomics reads to genes with annotated functions. We demonstrate the use of this method with data from a study of liver disease and synthetic reads, and Human Microbiome Project shotgun data, to detect differentially abundant Kyoto Encyclopedia of Genes and Genomes gene functions in these experiments. This rapid annotation method is freely available as a Galaxy workflow within a Docker image.

Pharmacomicrobiomics: The holy grail to variability in drug response?.

Clinical pharmacology and therapeutics [Epub ahead of print].

The human body, with 3.0×1013 cells and more than 3.8×1013 microorganisms, has nearly a one-to-one ratio of resident microbes to human cells. Initiatives like the Human Microbiome Project, American Gut, and Flemish Gut have identified associations between microbial taxa and human health. The study of interactions between microbiome and pharmaceutical agents i.e. pharamacomicrobiomics has revealed an instrumental role of the microbiome in modulating drug response that alters the therapeutic outcomes. In this review, we present our current comprehension of the relationship of the microbiome, host biology, and pharmaceutical agents such as cardiovascular drugs, analgesics and chemotherapeutic-agents to human disease and treatment outcomes. We also discuss the significance of studying diet-gene-drug interactions and further address the key challenges associated with pharamacomicrobiomics. Finally, we examine proposed models employing systems biology for the application of pharmacomicrobiomics and other omics data, and provide approaches to elucidate microbiome-drug interactions to improve future translation to personalized medicine. This article is protected by copyright. All rights reserved.

@article {pmid30937887,
year = {2019},
author = {Sharma, A and Buschmann, MM and Gilbert, JA},
title = {Pharmacomicrobiomics: The holy grail to variability in drug response?.},
journal = {Clinical pharmacology and therapeutics},
volume = {},
number = {},
pages = {},
doi = {10.1002/cpt.1437},
pmid = {30937887},
issn = {1532-6535},
abstract = {The human body, with 3.0×1013 cells and more than 3.8×1013 microorganisms, has nearly a one-to-one ratio of resident microbes to human cells. Initiatives like the Human Microbiome Project, American Gut, and Flemish Gut have identified associations between microbial taxa and human health. The study of interactions between microbiome and pharmaceutical agents i.e. pharamacomicrobiomics has revealed an instrumental role of the microbiome in modulating drug response that alters the therapeutic outcomes. In this review, we present our current comprehension of the relationship of the microbiome, host biology, and pharmaceutical agents such as cardiovascular drugs, analgesics and chemotherapeutic-agents to human disease and treatment outcomes. We also discuss the significance of studying diet-gene-drug interactions and further address the key challenges associated with pharamacomicrobiomics. Finally, we examine proposed models employing systems biology for the application of pharmacomicrobiomics and other omics data, and provide approaches to elucidate microbiome-drug interactions to improve future translation to personalized medicine. This article is protected by copyright. All rights reserved.},
}

RevDate: 2019-04-01

Greene LK, Bornbusch SL, McKenney EA, et al (2019)

The importance of scale in comparative microbiome research: New insights from the gut and glands of captive and wild lemurs.

American journal of primatology [Epub ahead of print].

Research on animal microbiomes is increasingly aimed at determining the evolutionary and ecological factors that govern host-microbiome dynamics, which are invariably intertwined and potentially synergistic. We present three empirical studies related to this topic, each of which relies on the diversity of Malagasy lemurs (representing a total of 19 species) and the comparative approach applied across scales of analysis. In Study 1, we compare gut microbial membership across 14 species in the wild to test the relative importance of host phylogeny and feeding strategy in mediating microbiome structure. Whereas host phylogeny strongly predicted community composition, the same feeding strategies shared by distant relatives did not produce convergent microbial consortia, but rather shaped microbiomes in host lineage-specific ways, particularly in folivores. In Study 2, we compare 14 species of wild and captive folivores, frugivores, and omnivores, to highlight the importance of captive populations for advancing gut microbiome research. We show that the perturbational effect of captivity is mediated by host feeding strategy and can be mitigated, in part, by modified animal management. In Study 3, we examine various scent-gland microbiomes across three species in the wild or captivity and show them to vary by host species, sex, body site, and a proxy of social status. These rare data provide support for the bacterial fermentation hypothesis in olfactory signal production and implicate steroid hormones as mediators of microbial community structure. We conclude by discussing the role of scale in comparative microbial studies, the links between feeding strategy and host-microbiome coadaptation, the underappreciated benefits of captive populations for advancing conservation research, and the need to consider the entirety of an animal's microbiota. Ultimately, these studies will help move the field from exploratory to hypothesis-driven research.

@article {pmid30932230,
year = {2019},
author = {Greene, LK and Bornbusch, SL and McKenney, EA and Harris, RL and Gorvetzian, SR and Yoder, AD and Drea, CM},
title = {The importance of scale in comparative microbiome research: New insights from the gut and glands of captive and wild lemurs.},
journal = {American journal of primatology},
volume = {},
number = {},
pages = {e22974},
doi = {10.1002/ajp.22974},
pmid = {30932230},
issn = {1098-2345},
support = {//Duke University/ ; //Margot Marsh Biodiversity Foundation/ ; //Duke Lemur Center/ ; 1749898//Division of Behavioral and Cognitive Sciences/ ; 1749465//Division of Behavioral and Cognitive Sciences/ ; },
abstract = {Research on animal microbiomes is increasingly aimed at determining the evolutionary and ecological factors that govern host-microbiome dynamics, which are invariably intertwined and potentially synergistic. We present three empirical studies related to this topic, each of which relies on the diversity of Malagasy lemurs (representing a total of 19 species) and the comparative approach applied across scales of analysis. In Study 1, we compare gut microbial membership across 14 species in the wild to test the relative importance of host phylogeny and feeding strategy in mediating microbiome structure. Whereas host phylogeny strongly predicted community composition, the same feeding strategies shared by distant relatives did not produce convergent microbial consortia, but rather shaped microbiomes in host lineage-specific ways, particularly in folivores. In Study 2, we compare 14 species of wild and captive folivores, frugivores, and omnivores, to highlight the importance of captive populations for advancing gut microbiome research. We show that the perturbational effect of captivity is mediated by host feeding strategy and can be mitigated, in part, by modified animal management. In Study 3, we examine various scent-gland microbiomes across three species in the wild or captivity and show them to vary by host species, sex, body site, and a proxy of social status. These rare data provide support for the bacterial fermentation hypothesis in olfactory signal production and implicate steroid hormones as mediators of microbial community structure. We conclude by discussing the role of scale in comparative microbial studies, the links between feeding strategy and host-microbiome coadaptation, the underappreciated benefits of captive populations for advancing conservation research, and the need to consider the entirety of an animal's microbiota. Ultimately, these studies will help move the field from exploratory to hypothesis-driven research.},
}

The microbiome, an intriguing component of the human body, composed of trillions of microorganisms, has prompted scientific exploration to identify and understand its function and role in health and disease. As associations between microbiome composition, disease, and symptoms accumulate, the future of medicine hinges upon a comprehensive knowledge of these microorganisms for patient care. The oral microbiome may provide valuable and efficient insight for predicting future changes in disease status, infection, or treatment course. The main aim of this pilot study was to characterize the oral microbiome in patients with severe aplastic anemia (SAA) during their therapeutic course. SAA is a hematologic disease characterized by bone marrow failure which if untreated is fatal. Treatment includes either hematopoietic stem cell transplantation (HSCT) or immunosuppressive therapy (IST). In this study, we examined the oral microbiome composition of 24 patients admitted to the National Institutes of Health (NIH) Clinical Center for experimental SAA treatment. Tongue brushings were collected to assess the effects of treatment on the oral microbiome. Twenty patients received standard IST (equine antithymocyte globulin and cyclosporine) plus eltrombopag. Four patients underwent HSCT. Oral specimens were obtained at three time points during treatment and clinical follow-up. Using a novel approach to 16S rRNA gene sequence analysis encompassing seven hypervariable regions, results demonstrated a predictable decrease in microbial diversity over time among the transplant patients. Linear discriminant analysis or LefSe reported a total of 14 statistically significant taxa (p < 0.05) across time points in the HSCT patients. One-way plots of relative abundance for two bacterial species (Haemophilus parainfluenzae and Rothia mucilaginosa) in the HSCT group, show the differences in abundance between time points. Only one bacterial species (Prevotella histicola) was noted in the IST group with a p value of 0.065. The patients receiving immunosuppressive therapy did not exhibit a clear change in diversity over time; however, patient-specific changes were noted. In addition, we compared our findings to tongue dorsum samples from healthy participants in the Human Microbiome Project (HMP) database and found among HSCT patients, approximately 35% of bacterial identifiers (N = 229) were unique to this study population and were not present in tongue dorsum specimens obtained from the HMP. Among IST-treated patients, 45% (N = 351) were unique to these patients and not identified by the HMP. Although antibiotic use may have likely influenced bacterial composition and diversity, some literature suggests a decreased impact of antimicrobials on the oral microbiome as compared to their effect on the gut microbiome. Future studies with larger sample sizes that focus on the oral microbiome and the effects of antibiotics in an immunosuppressed patient population may help establish these potential associations.

@article {pmid30919073,
year = {2019},
author = {Ames, NJ and Barb, JJ and Ranucci, A and Kim, H and Mudra, SE and Cashion, AK and Townsley, DM and Childs, R and Paster, BJ and Faller, LL and Wallen, GR},
title = {The oral microbiome of patients undergoing treatment for severe aplastic anemia: a pilot study.},
journal = {Annals of hematology},
volume = {},
number = {},
pages = {},
doi = {10.1007/s00277-019-03599-w},
pmid = {30919073},
issn = {1432-0584},
abstract = {The microbiome, an intriguing component of the human body, composed of trillions of microorganisms, has prompted scientific exploration to identify and understand its function and role in health and disease. As associations between microbiome composition, disease, and symptoms accumulate, the future of medicine hinges upon a comprehensive knowledge of these microorganisms for patient care. The oral microbiome may provide valuable and efficient insight for predicting future changes in disease status, infection, or treatment course. The main aim of this pilot study was to characterize the oral microbiome in patients with severe aplastic anemia (SAA) during their therapeutic course. SAA is a hematologic disease characterized by bone marrow failure which if untreated is fatal. Treatment includes either hematopoietic stem cell transplantation (HSCT) or immunosuppressive therapy (IST). In this study, we examined the oral microbiome composition of 24 patients admitted to the National Institutes of Health (NIH) Clinical Center for experimental SAA treatment. Tongue brushings were collected to assess the effects of treatment on the oral microbiome. Twenty patients received standard IST (equine antithymocyte globulin and cyclosporine) plus eltrombopag. Four patients underwent HSCT. Oral specimens were obtained at three time points during treatment and clinical follow-up. Using a novel approach to 16S rRNA gene sequence analysis encompassing seven hypervariable regions, results demonstrated a predictable decrease in microbial diversity over time among the transplant patients. Linear discriminant analysis or LefSe reported a total of 14 statistically significant taxa (p < 0.05) across time points in the HSCT patients. One-way plots of relative abundance for two bacterial species (Haemophilus parainfluenzae and Rothia mucilaginosa) in the HSCT group, show the differences in abundance between time points. Only one bacterial species (Prevotella histicola) was noted in the IST group with a p value of 0.065. The patients receiving immunosuppressive therapy did not exhibit a clear change in diversity over time; however, patient-specific changes were noted. In addition, we compared our findings to tongue dorsum samples from healthy participants in the Human Microbiome Project (HMP) database and found among HSCT patients, approximately 35% of bacterial identifiers (N = 229) were unique to this study population and were not present in tongue dorsum specimens obtained from the HMP. Among IST-treated patients, 45% (N = 351) were unique to these patients and not identified by the HMP. Although antibiotic use may have likely influenced bacterial composition and diversity, some literature suggests a decreased impact of antimicrobials on the oral microbiome as compared to their effect on the gut microbiome. Future studies with larger sample sizes that focus on the oral microbiome and the effects of antibiotics in an immunosuppressed patient population may help establish these potential associations.},
}

Environment and diet are key factors which shape the microbiome of organisms. There is also a disparity between captive and wild animals of the same species, presumably because of the change in diet. Being able to reverse the microbiome to the wild type is thus particularly important for the reintroduction efforts of Critically Endangered animals. The Javan slow loris (Nycticebus javanicus) is a suitable model, being kept in the thousands within rescue centres throughout Southeast Asia. With next-generation sequencing, we show how a naturalistic diet impacts the gut microbiome of captive slow lorises (Primates: Nycticebus). A comparison of the microbiome of wild animals with captive animals that had been fed a standard captive or improved diet reveals strong microbiome differences between wild and captive animals; however, diet changes failed to alter the microbiome of captive populations significantly. Bifidobacterium was the most abundant genus in wild animals (46.7%) while Bacteroides (11.6%) and Prevotella (18.9%) were the most abundant in captive animals fed the captive and improved diets, respectively. Correlation analyses of nutrients with microbial taxa suggest important implications in using nutrition to suppress potential pathogens, with soluble fibre and water-soluble carbohydrates both being associated with opposing microbiome profiles. The improved diet significantly increased microbe diversity, which exemplifies the importance of high fibre diets; however, wild individuals had lower diversity, which contradicts recent studies. Detection of methanogens appeared to be dependent on diet and whether the animals were living in captivity or in the wild. This study highlights the potential of nutrition in modulating the microbiome of animals prior to release. Unexpectedly, the results were not as significant as has been suggested in recent studies.

@article {pmid30858577,
year = {2019},
author = {Cabana, F and Clayton, JB and Nekaris, KAI and Wirdateti, W and Knights, D and Seedorf, H},
title = {Nutrient-based diet modifications impact on the gut microbiome of the Javan slow loris (Nycticebus javanicus).},
journal = {Scientific reports},
volume = {9},
number = {1},
pages = {4078},
doi = {10.1038/s41598-019-40911-0},
pmid = {30858577},
issn = {2045-2322},
support = {GEFNE101-13//National Geographic Society/ ; },
abstract = {Environment and diet are key factors which shape the microbiome of organisms. There is also a disparity between captive and wild animals of the same species, presumably because of the change in diet. Being able to reverse the microbiome to the wild type is thus particularly important for the reintroduction efforts of Critically Endangered animals. The Javan slow loris (Nycticebus javanicus) is a suitable model, being kept in the thousands within rescue centres throughout Southeast Asia. With next-generation sequencing, we show how a naturalistic diet impacts the gut microbiome of captive slow lorises (Primates: Nycticebus). A comparison of the microbiome of wild animals with captive animals that had been fed a standard captive or improved diet reveals strong microbiome differences between wild and captive animals; however, diet changes failed to alter the microbiome of captive populations significantly. Bifidobacterium was the most abundant genus in wild animals (46.7%) while Bacteroides (11.6%) and Prevotella (18.9%) were the most abundant in captive animals fed the captive and improved diets, respectively. Correlation analyses of nutrients with microbial taxa suggest important implications in using nutrition to suppress potential pathogens, with soluble fibre and water-soluble carbohydrates both being associated with opposing microbiome profiles. The improved diet significantly increased microbe diversity, which exemplifies the importance of high fibre diets; however, wild individuals had lower diversity, which contradicts recent studies. Detection of methanogens appeared to be dependent on diet and whether the animals were living in captivity or in the wild. This study highlights the potential of nutrition in modulating the microbiome of animals prior to release. Unexpectedly, the results were not as significant as has been suggested in recent studies.},
}

RevDate: 2019-03-05

Rego S, Dagan-Rosenfeld O, Bivona SA, et al (2019)

Much ado about nothing: A qualitative study of the experiences of an average-risk population receiving results of exome sequencing.

Journal of genetic counseling [Epub ahead of print].

The increasing availability of exome sequencing to the general ("healthy") population raises questions about the implications of genomic testing for individuals without suspected Mendelian diseases. Little is known about this population's motivations for undergoing exome sequencing, their expectations, reactions, and perceptions of utility. In order to address these questions, we conducted in-depth semi-structured interviews with 12 participants recruited from a longitudinal multi-omics profiling study that included exome sequencing. Participants were interviewed after receiving exome results, which included Mendelian disease-associated pathogenic and likely pathogenic variants, pharmacogenetic variants, and risk assessments for multifactorial diseases such as type 2 diabetes. The primary motivation driving participation in exome sequencing was personal curiosity. While they reported feeling validation and relief, participants were frequently underwhelmed by the results and described having expected more from exome sequencing. All participants reported discussing the results with at least some family, friends, and healthcare providers. Participants' recollection of the results returned to them was sometimes incorrect or incomplete, in many cases aligning with their perceptions of their health risks when entering the study. These results underscore the need for different genetic counseling approaches for generally healthy patients undergoing exome sequencing, in particular the need to provide anticipatory guidance to moderate participants' expectations. They also provide a preview of potential challenges clinicians may face as genomic sequencing continues to scale-up in the general population despite a lack of full understanding of its impact.

@article {pmid30835913,
year = {2019},
author = {Rego, S and Dagan-Rosenfeld, O and Bivona, SA and Snyder, MP and Ormond, KE},
title = {Much ado about nothing: A qualitative study of the experiences of an average-risk population receiving results of exome sequencing.},
journal = {Journal of genetic counseling},
volume = {},
number = {},
pages = {},
doi = {10.1002/jgc4.1096},
pmid = {30835913},
issn = {1573-3599},
support = {1U54DE02378901//NIH Common Fund Human Microbiome Project (HMP)/ ; 1-14-TS-28//American Diabetes Association/ ; 1-11-CT-35//American Diabetes Association/ ; },
abstract = {The increasing availability of exome sequencing to the general ("healthy") population raises questions about the implications of genomic testing for individuals without suspected Mendelian diseases. Little is known about this population's motivations for undergoing exome sequencing, their expectations, reactions, and perceptions of utility. In order to address these questions, we conducted in-depth semi-structured interviews with 12 participants recruited from a longitudinal multi-omics profiling study that included exome sequencing. Participants were interviewed after receiving exome results, which included Mendelian disease-associated pathogenic and likely pathogenic variants, pharmacogenetic variants, and risk assessments for multifactorial diseases such as type 2 diabetes. The primary motivation driving participation in exome sequencing was personal curiosity. While they reported feeling validation and relief, participants were frequently underwhelmed by the results and described having expected more from exome sequencing. All participants reported discussing the results with at least some family, friends, and healthcare providers. Participants' recollection of the results returned to them was sometimes incorrect or incomplete, in many cases aligning with their perceptions of their health risks when entering the study. These results underscore the need for different genetic counseling approaches for generally healthy patients undergoing exome sequencing, in particular the need to provide anticipatory guidance to moderate participants' expectations. They also provide a preview of potential challenges clinicians may face as genomic sequencing continues to scale-up in the general population despite a lack of full understanding of its impact.},
}

RevDate: 2019-03-05

Meyer F, Bremges A, Belmann P, et al (2019)

Assessing taxonomic metagenome profilers with OPAL.

Genome biology, 20(1):51 pii:10.1186/s13059-019-1646-y.

The explosive growth in taxonomic metagenome profiling methods over the past years has created a need for systematic comparisons using relevant performance criteria. The Open-community Profiling Assessment tooL (OPAL) implements commonly used performance metrics, including those of the first challenge of the initiative for the Critical Assessment of Metagenome Interpretation (CAMI), together with convenient visualizations. In addition, we perform in-depth performance comparisons with seven profilers on datasets of CAMI and the Human Microbiome Project. OPAL is freely available at https://github.com/CAMI-challenge/OPAL .

@article {pmid30832730,
year = {2019},
author = {Meyer, F and Bremges, A and Belmann, P and Janssen, S and McHardy, AC and Koslicki, D},
title = {Assessing taxonomic metagenome profilers with OPAL.},
journal = {Genome biology},
volume = {20},
number = {1},
pages = {51},
doi = {10.1186/s13059-019-1646-y},
pmid = {30832730},
issn = {1474-760X},
abstract = {The explosive growth in taxonomic metagenome profiling methods over the past years has created a need for systematic comparisons using relevant performance criteria. The Open-community Profiling Assessment tooL (OPAL) implements commonly used performance metrics, including those of the first challenge of the initiative for the Critical Assessment of Metagenome Interpretation (CAMI), together with convenient visualizations. In addition, we perform in-depth performance comparisons with seven profilers on datasets of CAMI and the Human Microbiome Project. OPAL is freely available at https://github.com/CAMI-challenge/OPAL .},
}

RevDate: 2019-02-28

Song Z, Wang X, Zhou X, et al (2019)

Taxonomic Distribution of FosB in Human-Microbiota and Activity Comparison of Fosfomycin Resistance.

Frontiers in microbiology, 10:200.

FosB, a Mg2+ dependent thioltransferase, confers antibiotic resistance to fosfomycin through enzymatic drug inactivation. Among all antibiotic resistant proteins in the Antibiotic Resistance Genes Database and the Comprehensive Antibiotic Resistance Database, FosB is within 5% of the most number of ARPs identified in Human Microbiome Project reference database but mainly distributed in limited genera, i.e., 122 of total 133 FosB homologues are found from Bacillus and Staphylococcus. Furthermore, these FosB sequences could be divided into three clusters based on their phylogenetic relationship, i.e., two groups of FosB were mainly from Bacillus, and another was mainly from Staphylococcus. Finally, we confirmed that FosB from the group of Staphylococcus presented the highest resistance ability to fosfomycin by in silico and in vitro comparisons. In summary, this study elaborates the specific taxonomic characteristics and resistant abilities of FosB in human microbiota, which might help in developing more promising fosfomycin-like antibiotics.

@article {pmid30814984,
year = {2019},
author = {Song, Z and Wang, X and Zhou, X and Jiang, S and Li, Y and Ahmad, O and Qi, L and Li, P and Li, J},
title = {Taxonomic Distribution of FosB in Human-Microbiota and Activity Comparison of Fosfomycin Resistance.},
journal = {Frontiers in microbiology},
volume = {10},
number = {},
pages = {200},
doi = {10.3389/fmicb.2019.00200},
pmid = {30814984},
issn = {1664-302X},
abstract = {FosB, a Mg2+ dependent thioltransferase, confers antibiotic resistance to fosfomycin through enzymatic drug inactivation. Among all antibiotic resistant proteins in the Antibiotic Resistance Genes Database and the Comprehensive Antibiotic Resistance Database, FosB is within 5% of the most number of ARPs identified in Human Microbiome Project reference database but mainly distributed in limited genera, i.e., 122 of total 133 FosB homologues are found from Bacillus and Staphylococcus. Furthermore, these FosB sequences could be divided into three clusters based on their phylogenetic relationship, i.e., two groups of FosB were mainly from Bacillus, and another was mainly from Staphylococcus. Finally, we confirmed that FosB from the group of Staphylococcus presented the highest resistance ability to fosfomycin by in silico and in vitro comparisons. In summary, this study elaborates the specific taxonomic characteristics and resistant abilities of FosB in human microbiota, which might help in developing more promising fosfomycin-like antibiotics.},
}

RevDate: 2019-02-27

NIH Human Microbiome Portfolio Analysis Team (2019)

A review of 10 years of human microbiome research activities at the US National Institutes of Health, Fiscal Years 2007-2016.

Microbiome, 7(1):31 pii:10.1186/s40168-019-0620-y.

The National Institutes of Health (NIH) is the primary federal government agency for biomedical research in the USA. NIH provides extensive support for human microbiome research with 21 of 27 NIH Institutes and Centers (ICs) currently funding this area through their extramural research programs. This analysis of the NIH extramural portfolio in human microbiome research briefly reviews the early history of this field at NIH, summarizes the program objectives and the resources developed in the recently completed 10-year (fiscal years 2007-2016) $215 M Human Microbiome Project (HMP) program, evaluates the scope and range of the $728 M NIH investment in extramural human microbiome research activities outside of the HMP over fiscal years 2012-2016, and highlights some specific areas of research which emerged from this investment. This analysis closes with a few comments on the technical needs and knowledge gaps which remain for this field to be able to advance over the next decade and for the outcomes of this research to be able to progress to microbiome-based interventions for treating disease and supporting health.

@article {pmid30808411,
year = {2019},
author = {, },
title = {A review of 10 years of human microbiome research activities at the US National Institutes of Health, Fiscal Years 2007-2016.},
journal = {Microbiome},
volume = {7},
number = {1},
pages = {31},
doi = {10.1186/s40168-019-0620-y},
pmid = {30808411},
issn = {2049-2618},
abstract = {The National Institutes of Health (NIH) is the primary federal government agency for biomedical research in the USA. NIH provides extensive support for human microbiome research with 21 of 27 NIH Institutes and Centers (ICs) currently funding this area through their extramural research programs. This analysis of the NIH extramural portfolio in human microbiome research briefly reviews the early history of this field at NIH, summarizes the program objectives and the resources developed in the recently completed 10-year (fiscal years 2007-2016) $215 M Human Microbiome Project (HMP) program, evaluates the scope and range of the $728 M NIH investment in extramural human microbiome research activities outside of the HMP over fiscal years 2012-2016, and highlights some specific areas of research which emerged from this investment. This analysis closes with a few comments on the technical needs and knowledge gaps which remain for this field to be able to advance over the next decade and for the outcomes of this research to be able to progress to microbiome-based interventions for treating disease and supporting health.},
}

RevDate: 2019-02-27

2017 NIH-wide microbiome workshop writing team (2019)

2017 NIH-wide workshop report on "The Human Microbiome: Emerging Themes at the Horizon of the 21st Century".

Microbiome, 7(1):32 pii:10.1186/s40168-019-0627-4.

The National Institutes of Health (NIH) organized a three-day human microbiome research workshop, August 16-18, 2017, to highlight the accomplishments of the 10-year Human Microbiome Project program, the outcomes of the investments made by the 21 NIH Institutes and Centers which now fund this area, and the technical challenges and knowledge gaps which will need to be addressed in order for this field to advance over the next 10 years. This report summarizes the key points in the talks, round table discussions, and Joint Agency Panel from this workshop.

@article {pmid30808401,
year = {2019},
author = {, },
title = {2017 NIH-wide workshop report on "The Human Microbiome: Emerging Themes at the Horizon of the 21st Century".},
journal = {Microbiome},
volume = {7},
number = {1},
pages = {32},
doi = {10.1186/s40168-019-0627-4},
pmid = {30808401},
issn = {2049-2618},
support = {U54HD080784//Eunice Kennedy Shriver National Institute of Child Health and Human Development/ ; U54DK102557//National Institute of Diabetes and Digestive and Kidney Diseases/ ; R24DK110499//National Institute of Diabetes and Digestive and Kidney Diseases/ ; U54DE023789//National Institute of Dental and Craniofacial Research/ ; },
abstract = {The National Institutes of Health (NIH) organized a three-day human microbiome research workshop, August 16-18, 2017, to highlight the accomplishments of the 10-year Human Microbiome Project program, the outcomes of the investments made by the 21 NIH Institutes and Centers which now fund this area, and the technical challenges and knowledge gaps which will need to be addressed in order for this field to advance over the next 10 years. This report summarizes the key points in the talks, round table discussions, and Joint Agency Panel from this workshop.},
}

The term microbiome describes the genetic material encoding the various microbial populations that inhabit our body. Whilst colonization of various body niches (e.g., the gut) by dynamic communities of microorganisms is now universally accepted, the existence of microbial populations in other "classically sterile" locations, including the blood, is a relatively new concept. The presence of bacteria-specific DNA in the blood has been reported in the literature for some time, yet the true origin of this is still the subject of much deliberation. The aim of this study was to investigate the phenomenon of a "blood microbiome" by providing a comprehensive description of bacterially derived nucleic acids using a range of complementary molecular and classical microbiological techniques. For this purpose we utilized a set of plasma samples from healthy subjects (n = 5) and asthmatic subjects (n = 5). DNA-level analyses involved the amplification and sequencing of the 16S rRNA gene. RNA-level analyses were based upon the de novo assembly of unmapped mRNA reads and subsequent taxonomic identification. Molecular studies were complemented by viability data from classical aerobic and anaerobic microbial culture experiments. At the phylum level, the blood microbiome was predominated by Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes. The key phyla detected were consistent irrespective of molecular method (DNA vs. RNA), and consistent with the results of other published studies. In silico comparison of our data with that of the Human Microbiome Project revealed that members of the blood microbiome were most likely to have originated from the oral or skin communities. To our surprise, aerobic and anaerobic cultures were positive in eight of out the ten donor samples investigated, and we reflect upon their source. Our data provide further evidence of a core blood microbiome, and provide insight into the potential source of the bacterial DNA/RNA detected in the blood. Further, data reveal the importance of robust experimental procedures, and identify areas for future consideration.

@article {pmid30705670,
year = {2018},
author = {Whittle, E and Leonard, MO and Harrison, R and Gant, TW and Tonge, DP},
title = {Multi-Method Characterization of the Human Circulating Microbiome.},
journal = {Frontiers in microbiology},
volume = {9},
number = {},
pages = {3266},
doi = {10.3389/fmicb.2018.03266},
pmid = {30705670},
issn = {1664-302X},
abstract = {The term microbiome describes the genetic material encoding the various microbial populations that inhabit our body. Whilst colonization of various body niches (e.g., the gut) by dynamic communities of microorganisms is now universally accepted, the existence of microbial populations in other "classically sterile" locations, including the blood, is a relatively new concept. The presence of bacteria-specific DNA in the blood has been reported in the literature for some time, yet the true origin of this is still the subject of much deliberation. The aim of this study was to investigate the phenomenon of a "blood microbiome" by providing a comprehensive description of bacterially derived nucleic acids using a range of complementary molecular and classical microbiological techniques. For this purpose we utilized a set of plasma samples from healthy subjects (n = 5) and asthmatic subjects (n = 5). DNA-level analyses involved the amplification and sequencing of the 16S rRNA gene. RNA-level analyses were based upon the de novo assembly of unmapped mRNA reads and subsequent taxonomic identification. Molecular studies were complemented by viability data from classical aerobic and anaerobic microbial culture experiments. At the phylum level, the blood microbiome was predominated by Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes. The key phyla detected were consistent irrespective of molecular method (DNA vs. RNA), and consistent with the results of other published studies. In silico comparison of our data with that of the Human Microbiome Project revealed that members of the blood microbiome were most likely to have originated from the oral or skin communities. To our surprise, aerobic and anaerobic cultures were positive in eight of out the ten donor samples investigated, and we reflect upon their source. Our data provide further evidence of a core blood microbiome, and provide insight into the potential source of the bacterial DNA/RNA detected in the blood. Further, data reveal the importance of robust experimental procedures, and identify areas for future consideration.},
}

RevDate: 2019-01-28

Waldron L, Schiffer L, Azhar R, et al (2019)

Improving Accessibility of the Human Microbiome Project Data Through Integration With R/Bioconductor.

The human gut microbiota encodes β-glucuronidases (GUS) that play key roles in health and disease via the metabolism of glucuronate-containing carbohydrates and drugs. Hundreds of putative bacterial GUS enzymes have been identified by metagenomic analysis of the human gut microbiome, but less than 10% have characterized structures and functions. Here we describe a set of unique gut microbial GUS enzymes that bind flavin mononucleotide (FMN). First, we show using mass spectrometry, isothermal titration calorimetry, and x-ray crystallography that a purified GUS from the gut commensal microbe Faecalibacterium prausnitzii binds to FMN on a surface groove located 30 Å away from the active site. Second, utilizing structural and functional data from this FMN-binding GUS, we analyzed the 279 unique GUS sequences from the human microbiome project database and identified 14 putative FMN-binding GUSs. We characterized four of these hits and solved the structure of two, the GUSs from Ruminococcus gnavus and Roseburia hominis, which confirmed that these are FMN binders. Third, binding and kinetic analysis of the FMN-binding site mutants of these five GUSs show that they utilize a conserved site to bind FMN that is not essential for GUS activity, but can affect KM. Lastly, a comprehensive structural review of the PDB reveals that the FMN-binding site employed by these enzymes is unlike any structurally characterized FMN-binders to date. These findings reveal the first instance of an FMN-binding glycoside hydrolase and suggest a potential link between FMN and carbohydrate metabolism in the human gut microbiota.

@article {pmid30658055,
year = {2019},
author = {Pellock, SJ and Walton, WG and Ervin, SM and Torres-Rivera, D and Creekmore, BC and Bergan, G and Dunn, ZD and Li, B and Tripathy, A and Redinbo, MR},
title = {Discovery and Characterization of FMN-Binding β-Glucuronidases in the Human Gut Microbiome.},
journal = {Journal of molecular biology},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.jmb.2019.01.013},
pmid = {30658055},
issn = {1089-8638},
abstract = {The human gut microbiota encodes β-glucuronidases (GUS) that play key roles in health and disease via the metabolism of glucuronate-containing carbohydrates and drugs. Hundreds of putative bacterial GUS enzymes have been identified by metagenomic analysis of the human gut microbiome, but less than 10% have characterized structures and functions. Here we describe a set of unique gut microbial GUS enzymes that bind flavin mononucleotide (FMN). First, we show using mass spectrometry, isothermal titration calorimetry, and x-ray crystallography that a purified GUS from the gut commensal microbe Faecalibacterium prausnitzii binds to FMN on a surface groove located 30 Å away from the active site. Second, utilizing structural and functional data from this FMN-binding GUS, we analyzed the 279 unique GUS sequences from the human microbiome project database and identified 14 putative FMN-binding GUSs. We characterized four of these hits and solved the structure of two, the GUSs from Ruminococcus gnavus and Roseburia hominis, which confirmed that these are FMN binders. Third, binding and kinetic analysis of the FMN-binding site mutants of these five GUSs show that they utilize a conserved site to bind FMN that is not essential for GUS activity, but can affect KM. Lastly, a comprehensive structural review of the PDB reveals that the FMN-binding site employed by these enzymes is unlike any structurally characterized FMN-binders to date. These findings reveal the first instance of an FMN-binding glycoside hydrolase and suggest a potential link between FMN and carbohydrate metabolism in the human gut microbiota.},
}

Alterations in the composition of the microbiota have been implicated in many diseases. The Human Microbiome Project (HMP) provides a comprehensive reference dataset of the "normal" human microbiome of 242 healthy adults at five major body sites. The HMP used both 16S ribosomal RNA gene sequencing and whole-genome metagenomic sequencing to profile the subjects' microbial communities. However, accessing and analyzing the HMP dataset still presents technical and bioinformatic challenges, as researchers must import the microbiome data, integrate phylogenetic trees, and access and merge public and restricted metadata. In this issue, the HMP16SData R/Bioconductor package developed by Schiffer and colleagues (Am J Epidemiol. XXX; XX (XX): XX-XXX) greatly simplifies access to the HMP data by combining 16S taxonomic abundance data, public patient metadata, and phylogenetic trees as a single data object. The authors also provide an interface for users with approved dbGaP projects to easily retrieve and merge the controlled-access HMP metadata. This package has a broad range of appeal to researchers across disciplines and with various levels of expertise in using R and/or other statistical tools. This will translate to improved data accessibility for public health research, with data from healthy individuals serving as a reference for disease-associated studies.

@article {pmid30649168,
year = {2019},
author = {Griffith, JC and Morgan, XC},
title = {Invited Commentary: Improving accessibility of the Human Microbiome Project data through integration with R/Bioconductor.},
journal = {American journal of epidemiology},
volume = {},
number = {},
pages = {},
doi = {10.1093/aje/kwz007},
pmid = {30649168},
issn = {1476-6256},
abstract = {Alterations in the composition of the microbiota have been implicated in many diseases. The Human Microbiome Project (HMP) provides a comprehensive reference dataset of the "normal" human microbiome of 242 healthy adults at five major body sites. The HMP used both 16S ribosomal RNA gene sequencing and whole-genome metagenomic sequencing to profile the subjects' microbial communities. However, accessing and analyzing the HMP dataset still presents technical and bioinformatic challenges, as researchers must import the microbiome data, integrate phylogenetic trees, and access and merge public and restricted metadata. In this issue, the HMP16SData R/Bioconductor package developed by Schiffer and colleagues (Am J Epidemiol. XXX; XX (XX): XX-XXX) greatly simplifies access to the HMP data by combining 16S taxonomic abundance data, public patient metadata, and phylogenetic trees as a single data object. The authors also provide an interface for users with approved dbGaP projects to easily retrieve and merge the controlled-access HMP metadata. This package has a broad range of appeal to researchers across disciplines and with various levels of expertise in using R and/or other statistical tools. This will translate to improved data accessibility for public health research, with data from healthy individuals serving as a reference for disease-associated studies.},
}

RevDate: 2019-01-16

Schiffer L, Azhar R, Shepherd L, et al (2019)

HMP16SData: Efficient Access to the Human Microbiome Project through Bioconductor.

American journal of epidemiology pii:5288094 [Epub ahead of print].

Phase 1 of the Human Microbiome Project (HMP) investigated 18 body subsites of 239 healthy American adults, to produce the first comprehensive reference for the composition and variation of the "healthy" human microbiome. Publicly-available data sets from amplicon sequencing of two 16S ribosomal RNA variable regions, with extensive controlled-access participant data, provide a reference for ongoing microbiome studies. However, utilization of these data sets can be hindered by the complex bioinformatic steps required to access, import, decrypt, and merge the various components in formats suitable for ecological and statistical analysis. The HMP16SData package provides count data for both 16S ribosomal RNA variable regions, integrated with phylogeny, taxonomy, public participant data, and controlled participant data for authorized researchers, using standard integrative Bioconductor data objects. By removing bioinformatic hurdles of data access and management, HMP16SData enables epidemiologists with only basic R skills to quickly analyze HMP data.

Members of the widespread bacterial phylum Chloroflexi can dominate high-microbial-abundance (HMA) sponge microbiomes. In the Sponge Microbiome Project, Chloroflexi sequences amounted to 20 to 30% of the total microbiome of certain HMA sponge genera with the classes/clades SAR202, Caldilineae, and Anaerolineae being the most prominent. We performed metagenomic and single-cell genomic analyses to elucidate the functional gene repertoire of Chloroflexi symbionts of Aplysina aerophoba. Eighteen draft genomes were reconstructed and placed into phylogenetic context of which six were investigated in detail. Common genomic features of Chloroflexi sponge symbionts were related to central energy and carbon converting pathways, amino acid and fatty acid metabolism, and respiration. Clade-specific metabolic features included a massively expanded genomic repertoire for carbohydrate degradation in Anaerolineae and Caldilineae genomes, but only amino acid utilization by SAR202. While Anaerolineae and Caldilineae import cofactors and vitamins, SAR202 genomes harbor genes encoding components involved in cofactor biosynthesis. A number of features relevant to symbiosis were further identified, including CRISPR-Cas systems, eukaryote-like repeat proteins, and secondary metabolite gene clusters. Chloroflexi symbionts were visualized in the sponge extracellular matrix at ultrastructural resolution by the fluorescence in situ hybridization-correlative light and electron microscopy (FISH-CLEM) method. Carbohydrate degradation potential was reported previously for "Candidatus Poribacteria" and SAUL, typical symbionts of HMA sponges, and we propose here that HMA sponge symbionts collectively engage in degradation of dissolved organic matter, both labile and recalcitrant. Thus, sponge microbes may not only provide nutrients to the sponge host, but they may also contribute to dissolved organic matter (DOM) recycling and primary productivity in reef ecosystems via a pathway termed the sponge loop. IMPORTANCEChloroflexi represent a widespread, yet enigmatic bacterial phylum with few cultivated members. We used metagenomic and single-cell genomic approaches to characterize the functional gene repertoire of Chloroflexi symbionts in marine sponges. The results of this study suggest clade-specific metabolic specialization and that Chloroflexi symbionts have the genomic potential for dissolved organic matter (DOM) degradation from seawater. Considering the abundance and dominance of sponges in many benthic environments, we predict that the role of sponge symbionts in biogeochemical cycles is larger than previously thought.

@article {pmid30637337,
year = {2018},
author = {Bayer, K and Jahn, MT and Slaby, BM and Moitinho-Silva, L and Hentschel, U},
title = {Marine Sponges as Chloroflexi Hot Spots: Genomic Insights and High-Resolution Visualization of an Abundant and Diverse Symbiotic Clade.},
journal = {mSystems},
volume = {3},
number = {6},
pages = {},
doi = {10.1128/mSystems.00150-18},
pmid = {30637337},
issn = {2379-5077},
abstract = {Members of the widespread bacterial phylum Chloroflexi can dominate high-microbial-abundance (HMA) sponge microbiomes. In the Sponge Microbiome Project, Chloroflexi sequences amounted to 20 to 30% of the total microbiome of certain HMA sponge genera with the classes/clades SAR202, Caldilineae, and Anaerolineae being the most prominent. We performed metagenomic and single-cell genomic analyses to elucidate the functional gene repertoire of Chloroflexi symbionts of Aplysina aerophoba. Eighteen draft genomes were reconstructed and placed into phylogenetic context of which six were investigated in detail. Common genomic features of Chloroflexi sponge symbionts were related to central energy and carbon converting pathways, amino acid and fatty acid metabolism, and respiration. Clade-specific metabolic features included a massively expanded genomic repertoire for carbohydrate degradation in Anaerolineae and Caldilineae genomes, but only amino acid utilization by SAR202. While Anaerolineae and Caldilineae import cofactors and vitamins, SAR202 genomes harbor genes encoding components involved in cofactor biosynthesis. A number of features relevant to symbiosis were further identified, including CRISPR-Cas systems, eukaryote-like repeat proteins, and secondary metabolite gene clusters. Chloroflexi symbionts were visualized in the sponge extracellular matrix at ultrastructural resolution by the fluorescence in situ hybridization-correlative light and electron microscopy (FISH-CLEM) method. Carbohydrate degradation potential was reported previously for "Candidatus Poribacteria" and SAUL, typical symbionts of HMA sponges, and we propose here that HMA sponge symbionts collectively engage in degradation of dissolved organic matter, both labile and recalcitrant. Thus, sponge microbes may not only provide nutrients to the sponge host, but they may also contribute to dissolved organic matter (DOM) recycling and primary productivity in reef ecosystems via a pathway termed the sponge loop. IMPORTANCEChloroflexi represent a widespread, yet enigmatic bacterial phylum with few cultivated members. We used metagenomic and single-cell genomic approaches to characterize the functional gene repertoire of Chloroflexi symbionts in marine sponges. The results of this study suggest clade-specific metabolic specialization and that Chloroflexi symbionts have the genomic potential for dissolved organic matter (DOM) degradation from seawater. Considering the abundance and dominance of sponges in many benthic environments, we predict that the role of sponge symbionts in biogeochemical cycles is larger than previously thought.},
}

RevDate: 2019-01-09

Zhai J, Knox K, Twigg HL, et al (2019)

Exact variance component tests for longitudinal microbiome studies.

Genetic epidemiology [Epub ahead of print].

In metagenomic studies, testing the association between microbiome composition and clinical outcomes translates to testing the nullity of variance components. Motivated by a lung human immunodeficiency virus (HIV) microbiome project, we study longitudinal microbiome data by using variance component models with more than two variance components. Current testing strategies only apply to models with exactly two variance components and when sample sizes are large. Therefore, they are not applicable to longitudinal microbiome studies. In this paper, we propose exact tests (score test, likelihood ratio test, and restricted likelihood ratio test) to (a) test the association of the overall microbiome composition in a longitudinal design and (b) detect the association of one specific microbiome cluster while adjusting for the effects from related clusters. Our approach combines the exact tests for null hypothesis with a single variance component with a strategy of reducing multiple variance components to a single one. Simulation studies demonstrate that our method has a correct type I error rate and superior power compared to existing methods at small sample sizes and weak signals. Finally, we apply our method to a longitudinal pulmonary microbiome study of HIV-infected patients and reveal two interesting genera Prevotella and Veillonella associated with forced vital capacity. Our findings shed light on the impact of the lung microbiome on HIV complexities. The method is implemented in the open-source, high-performance computing language Julia and is freely available at https://github.com/JingZhai63/VCmicrobiome.

Resources available in the human nasal cavity are limited. Therefore, to successfully colonize the nasal cavity, bacteria must compete for scarce nutrients. Competition may occur directly through interference (e.g., antibiotics) or indirectly by nutrient sequestration. To investigate the nature of nasal bacterial competition, we performed co-culture inhibition assays between nasal Actinobacteria and Staphylococcus spp. We found that coagulase-negative staphylococci (CoNS) isolates were sensitive to growth inhibition by Actinobacteria but Staphylococcus aureus isolates were resistant to inhibition. Among Actinobacteria, we observed that Corynebacterium spp. were variable in their ability to inhibit CoNS. We sequenced the genomes of ten Corynebacterium spp. isolates, including three Corynebacterium propinquum that strongly inhibited CoNS and seven other Corynebacterium spp. isolates that only weakly inhibited CoNS Using a comparative genomics approach, we found that the C. propinquum genomes were enriched in genes for iron acquisition and encoded a biosynthetic gene cluster (BGC) for siderophore production, absent in the non-inhibitory Corynebacterium spp. genomes. Using a chromeazurol S assay, we confirmed that C. propinquum produced siderophores. We demonstrated that iron supplementation rescued CoNS from inhibition by C. propinquum, suggesting that inhibition was due to iron restriction through siderophore production. Through comparative metabolomics and molecular networking, we identified the siderophore produced by C. propinquum as dehydroxynocardamine. Finally, we confirmed that the dehydroxynocardamine BGC is expressed in vivo by analyzing human nasal metatranscriptomes from the NIH Human Microbiome Project. Together, our results suggest that bacteria produce siderophores to compete for limited available iron in the nasal cavity and improve their fitness.IMPORTANCE Within the nasal cavity, interference competition through antimicrobial production is prevalent. For instance, nasal Staphylococcus spp. strains can inhibit the growth of other bacteria through the production of nonribosomal peptides and ribosomally synthesized and post-translationally modified peptides. In contrast, bacteria engaging in exploitation competition modify the external environment to prevent competitors from growing, usually by depleting access to essential nutrients. As the nasal cavity is a nutrient limited environment, we hypothesized that exploitation competition occurs in this system. We determined that Corynebacterium propinquum produces an iron-chelating siderophore and this iron-sequestering molecule correlates with the ability to inhibit the growth of coagulase-negative staphylococci. Further, we found that the genes required for siderophore production are expressed in vivo Thus, though siderophore production by bacteria is often considered a virulence trait, our work indicates that bacteria may produce siderophores to compete for limited iron in the human nasal cavity.

@article {pmid30578265,
year = {2018},
author = {Stubbendieck, RM and May, DS and Chevrette, MG and Temkin, MI and Wendt-Pienkowski, E and Cagnazzo, J and Carlson, CM and Gern, JE and Currie, CR},
title = {Competition among nasal bacteria suggests a role for siderophore-mediated interactions in shaping the human nasal microbiota.},
journal = {Applied and environmental microbiology},
volume = {},
number = {},
pages = {},
doi = {10.1128/AEM.02406-18},
pmid = {30578265},
issn = {1098-5336},
abstract = {Resources available in the human nasal cavity are limited. Therefore, to successfully colonize the nasal cavity, bacteria must compete for scarce nutrients. Competition may occur directly through interference (e.g., antibiotics) or indirectly by nutrient sequestration. To investigate the nature of nasal bacterial competition, we performed co-culture inhibition assays between nasal Actinobacteria and Staphylococcus spp. We found that coagulase-negative staphylococci (CoNS) isolates were sensitive to growth inhibition by Actinobacteria but Staphylococcus aureus isolates were resistant to inhibition. Among Actinobacteria, we observed that Corynebacterium spp. were variable in their ability to inhibit CoNS. We sequenced the genomes of ten Corynebacterium spp. isolates, including three Corynebacterium propinquum that strongly inhibited CoNS and seven other Corynebacterium spp. isolates that only weakly inhibited CoNS Using a comparative genomics approach, we found that the C. propinquum genomes were enriched in genes for iron acquisition and encoded a biosynthetic gene cluster (BGC) for siderophore production, absent in the non-inhibitory Corynebacterium spp. genomes. Using a chromeazurol S assay, we confirmed that C. propinquum produced siderophores. We demonstrated that iron supplementation rescued CoNS from inhibition by C. propinquum, suggesting that inhibition was due to iron restriction through siderophore production. Through comparative metabolomics and molecular networking, we identified the siderophore produced by C. propinquum as dehydroxynocardamine. Finally, we confirmed that the dehydroxynocardamine BGC is expressed in vivo by analyzing human nasal metatranscriptomes from the NIH Human Microbiome Project. Together, our results suggest that bacteria produce siderophores to compete for limited available iron in the nasal cavity and improve their fitness.IMPORTANCE Within the nasal cavity, interference competition through antimicrobial production is prevalent. For instance, nasal Staphylococcus spp. strains can inhibit the growth of other bacteria through the production of nonribosomal peptides and ribosomally synthesized and post-translationally modified peptides. In contrast, bacteria engaging in exploitation competition modify the external environment to prevent competitors from growing, usually by depleting access to essential nutrients. As the nasal cavity is a nutrient limited environment, we hypothesized that exploitation competition occurs in this system. We determined that Corynebacterium propinquum produces an iron-chelating siderophore and this iron-sequestering molecule correlates with the ability to inhibit the growth of coagulase-negative staphylococci. Further, we found that the genes required for siderophore production are expressed in vivo Thus, though siderophore production by bacteria is often considered a virulence trait, our work indicates that bacteria may produce siderophores to compete for limited iron in the human nasal cavity.},
}

Proceedings of the National Academy of Sciences of the United States of America pii:1810840115 [Epub ahead of print].

Bystander selection-the selective pressure for resistance exerted by antibiotics on microbes that are not the target pathogen of treatment-is critical to understanding the total impact of broad-spectrum antibiotic use on pathogenic bacterial species that are often carried asymptomatically. However, to our knowledge, this effect has never been quantified. We quantify bystander selection for resistance for a range of clinically relevant antibiotic-species pairs as the proportion of all antibiotic exposures received by a species for conditions in which that species was not the causative pathogen ("proportion of bystander exposures"). Data sources include the 2010-2011 National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey, the Human Microbiome Project, and additional carriage and etiological data from existing literature. For outpatient prescribing in the United States, we find that this proportion over all included antibiotic classes is over 80% for eight of nine organisms of interest. Low proportions of bystander exposure are often associated with infrequent bacterial carriage or concentrated prescribing of a particular antibiotic for conditions caused by the species of interest. Applying our results, we roughly estimate that pneumococcal conjugate vaccination programs result in nearly the same proportional reduction in total antibiotic exposures of Streptococcus pneumoniae, Staphylococcus aureus, and Escherichia coli, despite the latter two organisms not being targeted by the vaccine. These results underscore the importance of considering antibiotic exposures of bystanders, in addition to the target pathogen, in measuring the impact of antibiotic resistance interventions.

@article {pmid30559213,
year = {2018},
author = {Tedijanto, C and Olesen, SW and Grad, YH and Lipsitch, M},
title = {Estimating the proportion of bystander selection for antibiotic resistance among potentially pathogenic bacterial flora.},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {},
number = {},
pages = {},
doi = {10.1073/pnas.1810840115},
pmid = {30559213},
issn = {1091-6490},
abstract = {Bystander selection-the selective pressure for resistance exerted by antibiotics on microbes that are not the target pathogen of treatment-is critical to understanding the total impact of broad-spectrum antibiotic use on pathogenic bacterial species that are often carried asymptomatically. However, to our knowledge, this effect has never been quantified. We quantify bystander selection for resistance for a range of clinically relevant antibiotic-species pairs as the proportion of all antibiotic exposures received by a species for conditions in which that species was not the causative pathogen ("proportion of bystander exposures"). Data sources include the 2010-2011 National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey, the Human Microbiome Project, and additional carriage and etiological data from existing literature. For outpatient prescribing in the United States, we find that this proportion over all included antibiotic classes is over 80% for eight of nine organisms of interest. Low proportions of bystander exposure are often associated with infrequent bacterial carriage or concentrated prescribing of a particular antibiotic for conditions caused by the species of interest. Applying our results, we roughly estimate that pneumococcal conjugate vaccination programs result in nearly the same proportional reduction in total antibiotic exposures of Streptococcus pneumoniae, Staphylococcus aureus, and Escherichia coli, despite the latter two organisms not being targeted by the vaccine. These results underscore the importance of considering antibiotic exposures of bystanders, in addition to the target pathogen, in measuring the impact of antibiotic resistance interventions.},
}

BACKGROUND: The aim of this study was to longitudinally investigate the prevalence and characterization of Campylobacter spp. from non-human primates primate (NHP) with a history of endemic diarrhea housed at Como Park Zoo.

METHODS: Fecal samples from 33 symptom-free NHP belonging to eight different species were collected weekly for 9 weeks. Species-level characterization and phylogenetic analysis of isolates included biochemical testing and 16S rRNA sequencing.

RESULTS: Campylobacter spp. were isolated from the feces of 42% (14/33) of the primates. Three Campylobacter spp. (C upsaliensis, C jejuni, and novel Campylobacter sp.) were identified from three NHP species. A possible positive host Campylobacter species-specificity was observed. However, no statistical association was observed between the isolation of Campylobacter spp. and age and sex of the animal.

CONCLUSIONS: The study revealed the value of conducting repeated fecal sampling to establish the overall prevalence of Campylobacter in zoo-maintained NHP; it also importantly identifies a novel Campylobacter sp. isolated from white-faced saki monkeys.

METHODS: Fecal samples from 33 symptom-free NHP belonging to eight different species were collected weekly for 9 weeks. Species-level characterization and phylogenetic analysis of isolates included biochemical testing and 16S rRNA sequencing.

RESULTS: Campylobacter spp. were isolated from the feces of 42% (14/33) of the primates. Three Campylobacter spp. (C upsaliensis, C jejuni, and novel Campylobacter sp.) were identified from three NHP species. A possible positive host Campylobacter species-specificity was observed. However, no statistical association was observed between the isolation of Campylobacter spp. and age and sex of the animal.

CONCLUSIONS: The study revealed the value of conducting repeated fecal sampling to establish the overall prevalence of Campylobacter in zoo-maintained NHP; it also importantly identifies a novel Campylobacter sp. isolated from white-faced saki monkeys.},
}

RevDate: 2018-12-11

Escapa IF, Chen T, Huang Y, et al (2018)

New Insights into Human Nostril Microbiome from the Expanded Human Oral Microbiome Database (eHOMD): a Resource for the Microbiome of the Human Aerodigestive Tract.

mSystems, 3(6): pii:mSystems00187-18.

The expanded Human Oral Microbiome Database (eHOMD) is a comprehensive microbiome database for sites along the human aerodigestive tract that revealed new insights into the nostril microbiome. The eHOMD provides well-curated 16S rRNA gene reference sequences linked to available genomes and enables assignment of species-level taxonomy to most next-generation sequences derived from diverse aerodigestive tract sites, including the nasal passages, sinuses, throat, esophagus, and mouth. Using minimum entropy decomposition coupled with the RDP Classifier and our eHOMD V1-V3 training set, we reanalyzed 16S rRNA V1-V3 sequences from the nostrils of 210 Human Microbiome Project participants at the species level, revealing four key insights. First, we discovered that Lawsonella clevelandensis, a recently named bacterium, and Neisseriaceae [G-1] HMT-174, a previously unrecognized bacterium, are common in adult nostrils. Second, just 19 species accounted for 90% of the total sequences from all participants. Third, 1 of these 19 species belonged to a currently uncultivated genus. Fourth, for 94% of the participants, 2 to 10 species constituted 90% of their sequences, indicating that the nostril microbiome may be represented by limited consortia. These insights highlight the strengths of the nostril microbiome as a model system for studying interspecies interactions and microbiome function. Also, in this cohort, three common nasal species (Dolosigranulum pigrum and two Corynebacterium species) showed positive differential abundance when the pathobiont Staphylococcus aureus was absent, generating hypotheses regarding colonization resistance. By facilitating species-level taxonomic assignment to microbes from the human aerodigestive tract, the eHOMD is a vital resource enhancing clinical relevance of microbiome studies. IMPORTANCE The eHOMD (http://www.ehomd.org) is a valuable resource for researchers, from basic to clinical, who study the microbiomes and the individual microbes in body sites in the human aerodigestive tract, which includes the nasal passages, sinuses, throat, esophagus, and mouth, and the lower respiratory tract, in health and disease. The eHOMD is an actively curated, web-based, open-access resource. eHOMD provides the following: (i) species-level taxonomy based on grouping 16S rRNA gene sequences at 98.5% identity, (ii) a systematic naming scheme for unnamed and/or uncultivated microbial taxa, (iii) reference genomes to facilitate metagenomic, metatranscriptomic, and proteomic studies and (iv) convenient cross-links to other databases (e.g., PubMed and Entrez). By facilitating the assignment of species names to sequences, the eHOMD is a vital resource for enhancing the clinical relevance of 16S rRNA gene-based microbiome studies, as well as metagenomic studies.

@article {pmid30534599,
year = {2018},
author = {Escapa, IF and Chen, T and Huang, Y and Gajare, P and Dewhirst, FE and Lemon, KP},
title = {New Insights into Human Nostril Microbiome from the Expanded Human Oral Microbiome Database (eHOMD): a Resource for the Microbiome of the Human Aerodigestive Tract.},
journal = {mSystems},
volume = {3},
number = {6},
pages = {},
doi = {10.1128/mSystems.00187-18},
pmid = {30534599},
issn = {2379-5077},
abstract = {The expanded Human Oral Microbiome Database (eHOMD) is a comprehensive microbiome database for sites along the human aerodigestive tract that revealed new insights into the nostril microbiome. The eHOMD provides well-curated 16S rRNA gene reference sequences linked to available genomes and enables assignment of species-level taxonomy to most next-generation sequences derived from diverse aerodigestive tract sites, including the nasal passages, sinuses, throat, esophagus, and mouth. Using minimum entropy decomposition coupled with the RDP Classifier and our eHOMD V1-V3 training set, we reanalyzed 16S rRNA V1-V3 sequences from the nostrils of 210 Human Microbiome Project participants at the species level, revealing four key insights. First, we discovered that Lawsonella clevelandensis, a recently named bacterium, and Neisseriaceae [G-1] HMT-174, a previously unrecognized bacterium, are common in adult nostrils. Second, just 19 species accounted for 90% of the total sequences from all participants. Third, 1 of these 19 species belonged to a currently uncultivated genus. Fourth, for 94% of the participants, 2 to 10 species constituted 90% of their sequences, indicating that the nostril microbiome may be represented by limited consortia. These insights highlight the strengths of the nostril microbiome as a model system for studying interspecies interactions and microbiome function. Also, in this cohort, three common nasal species (Dolosigranulum pigrum and two Corynebacterium species) showed positive differential abundance when the pathobiont Staphylococcus aureus was absent, generating hypotheses regarding colonization resistance. By facilitating species-level taxonomic assignment to microbes from the human aerodigestive tract, the eHOMD is a vital resource enhancing clinical relevance of microbiome studies. IMPORTANCE The eHOMD (http://www.ehomd.org) is a valuable resource for researchers, from basic to clinical, who study the microbiomes and the individual microbes in body sites in the human aerodigestive tract, which includes the nasal passages, sinuses, throat, esophagus, and mouth, and the lower respiratory tract, in health and disease. The eHOMD is an actively curated, web-based, open-access resource. eHOMD provides the following: (i) species-level taxonomy based on grouping 16S rRNA gene sequences at 98.5% identity, (ii) a systematic naming scheme for unnamed and/or uncultivated microbial taxa, (iii) reference genomes to facilitate metagenomic, metatranscriptomic, and proteomic studies and (iv) convenient cross-links to other databases (e.g., PubMed and Entrez). By facilitating the assignment of species names to sequences, the eHOMD is a vital resource for enhancing the clinical relevance of 16S rRNA gene-based microbiome studies, as well as metagenomic studies.},
}

Military-Related Exposures, Social Determinants of Health, and Dysbiosis: The United States-Veteran Microbiome Project (US-VMP).

Frontiers in cellular and infection microbiology, 8:400.

Significant effort has been put forth to increase understanding regarding the role of the human microbiome in health- and disease-related processes. In turn, the United States (US) Veteran Microbiome Project (US-VMP) was conceptualized as a means by which to serially collect microbiome and health-related data from those seeking care within the Veterans Health Administration (VHA). In this manuscript, exposures related to military experiences, as well as conditions and health-related factors among patients seen in VHA clinical settings are discussed in relation to common psychological and physical outcomes. Upon enrollment in the study, Veterans complete psychometrically sound (i.e., reliable and valid) measures regarding their past and current medical history. Participants also provide skin, oral, and gut microbiome samples, and permission to track their health status via the VHA electronic medical record. To date, data collection efforts have been cross-diagnostic. Within this manuscript, we describe current data collection practices and procedures, as well as highlight demographic, military, and psychiatric characteristics of the first 188 Veterans enrolled in the study. Based on these findings, we assert that this cohort is unique as compared to those enrolled in recent large-scale studies of the microbiome. To increase understanding regarding disease and health among diverse cohorts, efforts such as the US-VMP are vital. Ongoing barriers and facilitators to data collection are discussed, as well as future research directions, with an emphasis on the importance of shifting current thinking regarding the microbiome from a focus on normalcy and dysbiosis to health promotion and disease prevention.

@article {pmid30510919,
year = {2018},
author = {Brenner, LA and Hoisington, AJ and Stearns-Yoder, KA and Stamper, CE and Heinze, JD and Postolache, TT and Hadidi, DA and Hoffmire, CA and Stanislawski, MA and Lowry, CA},
title = {Military-Related Exposures, Social Determinants of Health, and Dysbiosis: The United States-Veteran Microbiome Project (US-VMP).},
journal = {Frontiers in cellular and infection microbiology},
volume = {8},
number = {},
pages = {400},
doi = {10.3389/fcimb.2018.00400},
pmid = {30510919},
issn = {2235-2988},
abstract = {Significant effort has been put forth to increase understanding regarding the role of the human microbiome in health- and disease-related processes. In turn, the United States (US) Veteran Microbiome Project (US-VMP) was conceptualized as a means by which to serially collect microbiome and health-related data from those seeking care within the Veterans Health Administration (VHA). In this manuscript, exposures related to military experiences, as well as conditions and health-related factors among patients seen in VHA clinical settings are discussed in relation to common psychological and physical outcomes. Upon enrollment in the study, Veterans complete psychometrically sound (i.e., reliable and valid) measures regarding their past and current medical history. Participants also provide skin, oral, and gut microbiome samples, and permission to track their health status via the VHA electronic medical record. To date, data collection efforts have been cross-diagnostic. Within this manuscript, we describe current data collection practices and procedures, as well as highlight demographic, military, and psychiatric characteristics of the first 188 Veterans enrolled in the study. Based on these findings, we assert that this cohort is unique as compared to those enrolled in recent large-scale studies of the microbiome. To increase understanding regarding disease and health among diverse cohorts, efforts such as the US-VMP are vital. Ongoing barriers and facilitators to data collection are discussed, as well as future research directions, with an emphasis on the importance of shifting current thinking regarding the microbiome from a focus on normalcy and dysbiosis to health promotion and disease prevention.},
}

Comparative studies of microbiome variation in world populations and different developmental stages of organisms are essential to decipher the linkages among microbiome, health, and disease. Notably, the gut microbiota are believed to mature in early life. In this context, we compared the gut microbiota diversity in Korean adolescent healthy samples (KAHSs) to healthy Korean adults (HKAs) as well as the Human Microbiome Project healthy samples (HMPHSs), the latter being one of the largest adult cohorts, based on organismal composition, alpha- and beta-diversities, function/pathway prediction analysis, and co-occurrence networks. We found that the gut microbiota compositions, including the ratios of firmicutes to bacteroidetes, between KAHSs and HMPHSs were different, and the diversities of KAHSs were less than those of HMPHSs. The predicted functions, for example, secondary bile acid synthesis and insulin signaling of KAHSs and HMPHSs, were also significantly different. Genus-level networks showed that co-occurrences among different taxa more frequently happened in HMPHSs than in KAHSs. Even though both KAHSs and HMPHSs represent healthy microbiomes, comparisons showed substantial differences, likely implicating different diets, environments, and demographics. Interestingly, we observed lower microbial diversities and less frequent co-occurrences among different taxa in KAHSs than adult HMPHSs and HKAs. These new findings collectively suggest that the adolescent gut microbiota in the present Korean sample did not reach the extent of maturity of adult microbiota diversity. In all, further population studies of microbiome variation across geographies and developmental stages are warranted, and should usefully inform future diagnostics and therapeutics innovation targeting the microbiome.

@article {pmid30481125,
year = {2018},
author = {Kim, JW and Lee, JS and Kim, JH and Jeong, JW and Lee, DH and Nam, S},
title = {Comparison of Microbiota Variation in Korean Healthy Adolescents with Adults Suggests Notable Maturity Differences.},
journal = {Omics : a journal of integrative biology},
volume = {},
number = {},
pages = {},
doi = {10.1089/omi.2018.0146},
pmid = {30481125},
issn = {1557-8100},
abstract = {Comparative studies of microbiome variation in world populations and different developmental stages of organisms are essential to decipher the linkages among microbiome, health, and disease. Notably, the gut microbiota are believed to mature in early life. In this context, we compared the gut microbiota diversity in Korean adolescent healthy samples (KAHSs) to healthy Korean adults (HKAs) as well as the Human Microbiome Project healthy samples (HMPHSs), the latter being one of the largest adult cohorts, based on organismal composition, alpha- and beta-diversities, function/pathway prediction analysis, and co-occurrence networks. We found that the gut microbiota compositions, including the ratios of firmicutes to bacteroidetes, between KAHSs and HMPHSs were different, and the diversities of KAHSs were less than those of HMPHSs. The predicted functions, for example, secondary bile acid synthesis and insulin signaling of KAHSs and HMPHSs, were also significantly different. Genus-level networks showed that co-occurrences among different taxa more frequently happened in HMPHSs than in KAHSs. Even though both KAHSs and HMPHSs represent healthy microbiomes, comparisons showed substantial differences, likely implicating different diets, environments, and demographics. Interestingly, we observed lower microbial diversities and less frequent co-occurrences among different taxa in KAHSs than adult HMPHSs and HKAs. These new findings collectively suggest that the adolescent gut microbiota in the present Korean sample did not reach the extent of maturity of adult microbiota diversity. In all, further population studies of microbiome variation across geographies and developmental stages are warranted, and should usefully inform future diagnostics and therapeutics innovation targeting the microbiome.},
}

The microbe is small in volume, but large in quantity and species. The symbiotic microbe, which is far more than human cells, code millions times of genes than human being. Somatic cells and these symbiotic microbe distributing in human body skin, respiratory tract, oral cavity and gastrointestinal tract, urinary tract and other parts form a complex ecosystem whose dynamic balance is highly related to body health. With the successful implementation of Human Microbiome Project, more attentions have been paid to the next generation microbiome technologies. New tools and methods for ecological regulation of human microbiome are emerging. The way we improve the world of human microbiology will be more convenient. This paper will make a review on the modulation techniques of human microbiome.

@article {pmid30465353,
year = {2018},
author = {Wang, H and Kang, D and Zhou, XD and Li, YQ},
title = {[Prevention of infectious diseases through microecology modulation techniques].},
journal = {Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology},
volume = {36},
number = {5},
pages = {564-567},
doi = {10.7518/hxkq.2018.05.018},
pmid = {30465353},
issn = {1000-1182},
abstract = {The microbe is small in volume, but large in quantity and species. The symbiotic microbe, which is far more than human cells, code millions times of genes than human being. Somatic cells and these symbiotic microbe distributing in human body skin, respiratory tract, oral cavity and gastrointestinal tract, urinary tract and other parts form a complex ecosystem whose dynamic balance is highly related to body health. With the successful implementation of Human Microbiome Project, more attentions have been paid to the next generation microbiome technologies. New tools and methods for ecological regulation of human microbiome are emerging. The way we improve the world of human microbiology will be more convenient. This paper will make a review on the modulation techniques of human microbiome.},
}

RevDate: 2018-11-19

Rajakovich LJ, EP Balskus (2018)

Metabolic functions of the human gut microbiota: the role of metalloenzymes.

Natural product reports [Epub ahead of print].

Covering: up to the end of 2017The human body is composed of an equal number of human and microbial cells. While the microbial community inhabiting the human gastrointestinal tract plays an essential role in host health, these organisms have also been connected to various diseases. Yet, the gut microbial functions that modulate host biology are not well established. In this review, we describe metabolic functions of the human gut microbiota that involve metalloenzymes. These activities enable gut microbial colonization, mediate interactions with the host, and impact human health and disease. We highlight cases in which enzyme characterization has advanced our understanding of the gut microbiota and examples that illustrate the diverse ways in which metalloenzymes facilitate both essential and unique functions of this community. Finally, we analyze Human Microbiome Project sequencing datasets to assess the distribution of a prominent family of metalloenzymes in human-associated microbial communities, guiding future enzyme characterization efforts.

@article {pmid30452039,
year = {2018},
author = {Rajakovich, LJ and Balskus, EP},
title = {Metabolic functions of the human gut microbiota: the role of metalloenzymes.},
journal = {Natural product reports},
volume = {},
number = {},
pages = {},
doi = {10.1039/c8np00074c},
pmid = {30452039},
issn = {1460-4752},
abstract = {Covering: up to the end of 2017The human body is composed of an equal number of human and microbial cells. While the microbial community inhabiting the human gastrointestinal tract plays an essential role in host health, these organisms have also been connected to various diseases. Yet, the gut microbial functions that modulate host biology are not well established. In this review, we describe metabolic functions of the human gut microbiota that involve metalloenzymes. These activities enable gut microbial colonization, mediate interactions with the host, and impact human health and disease. We highlight cases in which enzyme characterization has advanced our understanding of the gut microbiota and examples that illustrate the diverse ways in which metalloenzymes facilitate both essential and unique functions of this community. Finally, we analyze Human Microbiome Project sequencing datasets to assess the distribution of a prominent family of metalloenzymes in human-associated microbial communities, guiding future enzyme characterization efforts.},
}

RevDate: 2018-11-16

Su X, Jing G, McDonald D, et al (2018)

Identifying and Predicting Novelty in Microbiome Studies.

mBio, 9(6): pii:mBio.02099-18.

With the expansion of microbiome sequencing globally, a key challenge is to relate new microbiome samples to the existing space of microbiome samples. Here, we present Microbiome Search Engine (MSE), which enables the rapid search of query microbiome samples against a large, well-curated reference microbiome database organized by taxonomic similarity at the whole-microbiome level. Tracking the microbiome novelty score (MNS) over 8 years of microbiome depositions based on searching in more than 100,000 global 16S rRNA gene amplicon samples, we detected that the structural novelty of human microbiomes is approaching saturation and likely bounded, whereas that in environmental habitats remains 5 times higher. Via the microbiome focus index (MFI), which is derived from the MNS and microbiome attention score (MAS), we objectively track and compare the structural-novelty and attracted-attention scores of individual microbiome samples and projects, and we predict future trends in the field. For example, marine and indoor environments and mother-baby interactions are likely to receive disproportionate additional attention based on recent trends. Therefore, MNS, MAS, and MFI are proposed "alt-metrics" for evaluating a microbiome project or prospective developments in the microbiome field, both of which are done in the context of existing microbiome big data.IMPORTANCE We introduce two concepts to quantify the novelty of a microbiome. The first, the microbiome novelty score (MNS), allows identification of microbiomes that are especially different from what is already sequenced. The second, the microbiome attention score (MAS), allows identification of microbiomes that have many close neighbors, implying that considerable scientific attention is devoted to their study. By computing a microbiome focus index based on the MNS and MAS, we objectively track and compare the novelty and attention scores of individual microbiome samples and projects over time and predict future trends in the field; i.e., we work toward yielding fundamentally new microbiomes rather than filling in the details. Therefore, MNS, MAS, and MFI can serve as "alt-metrics" for evaluating a microbiome project or prospective developments in the microbiome field, both of which are done in the context of existing microbiome big data.

@article {pmid30425147,
year = {2018},
author = {Su, X and Jing, G and McDonald, D and Wang, H and Wang, Z and Gonzalez, A and Sun, Z and Huang, S and Navas, J and Knight, R and Xu, J},
title = {Identifying and Predicting Novelty in Microbiome Studies.},
journal = {mBio},
volume = {9},
number = {6},
pages = {},
doi = {10.1128/mBio.02099-18},
pmid = {30425147},
issn = {2150-7511},
abstract = {With the expansion of microbiome sequencing globally, a key challenge is to relate new microbiome samples to the existing space of microbiome samples. Here, we present Microbiome Search Engine (MSE), which enables the rapid search of query microbiome samples against a large, well-curated reference microbiome database organized by taxonomic similarity at the whole-microbiome level. Tracking the microbiome novelty score (MNS) over 8 years of microbiome depositions based on searching in more than 100,000 global 16S rRNA gene amplicon samples, we detected that the structural novelty of human microbiomes is approaching saturation and likely bounded, whereas that in environmental habitats remains 5 times higher. Via the microbiome focus index (MFI), which is derived from the MNS and microbiome attention score (MAS), we objectively track and compare the structural-novelty and attracted-attention scores of individual microbiome samples and projects, and we predict future trends in the field. For example, marine and indoor environments and mother-baby interactions are likely to receive disproportionate additional attention based on recent trends. Therefore, MNS, MAS, and MFI are proposed "alt-metrics" for evaluating a microbiome project or prospective developments in the microbiome field, both of which are done in the context of existing microbiome big data.IMPORTANCE We introduce two concepts to quantify the novelty of a microbiome. The first, the microbiome novelty score (MNS), allows identification of microbiomes that are especially different from what is already sequenced. The second, the microbiome attention score (MAS), allows identification of microbiomes that have many close neighbors, implying that considerable scientific attention is devoted to their study. By computing a microbiome focus index based on the MNS and MAS, we objectively track and compare the novelty and attention scores of individual microbiome samples and projects over time and predict future trends in the field; i.e., we work toward yielding fundamentally new microbiomes rather than filling in the details. Therefore, MNS, MAS, and MFI can serve as "alt-metrics" for evaluating a microbiome project or prospective developments in the microbiome field, both of which are done in the context of existing microbiome big data.},
}

RevDate: 2018-11-15

Frioux C, Fremy E, Trottier C, et al (2018)

Scalable and exhaustive screening of metabolic functions carried out by microbial consortia.

Bioinformatics (Oxford, England), 34(17):i934-i943.

Motivation: The selection of species exhibiting metabolic behaviors of interest is a challenging step when switching from the investigation of a large microbiota to the study of functions effectiveness. Approaches based on a compartmentalized framework are not scalable. The output of scalable approaches based on a non-compartmentalized modeling may be so large that it has neither been explored nor handled so far.

Results: We present the Miscoto tool to facilitate the selection of a community optimizing a desired function in a microbiome by reporting several possibilities which can be then sorted according to biological criteria. Communities are exhaustively identified using logical programming and by combining the non-compartmentalized and the compartmentalized frameworks. The benchmarking of 4.9 million metabolic functions associated with the Human Microbiome Project, shows that Miscoto is suited to screen and classify metabolic producibility in terms of feasibility, functional redundancy and cooperation processes involved. As an illustration of a host-microbial system, screening the Recon 2.2 human metabolism highlights the role of different consortia within a family of 773 intestinal bacteria.

Miscoto source code, instructions for use and examples are available at: https://github.com/cfrioux/miscoto.

@article {pmid30423063,
year = {2018},
author = {Frioux, C and Fremy, E and Trottier, C and Siegel, A},
title = {Scalable and exhaustive screening of metabolic functions carried out by microbial consortia.},
journal = {Bioinformatics (Oxford, England)},
volume = {34},
number = {17},
pages = {i934-i943},
doi = {10.1093/bioinformatics/bty588},
pmid = {30423063},
issn = {1367-4811},
abstract = {Motivation: The selection of species exhibiting metabolic behaviors of interest is a challenging step when switching from the investigation of a large microbiota to the study of functions effectiveness. Approaches based on a compartmentalized framework are not scalable. The output of scalable approaches based on a non-compartmentalized modeling may be so large that it has neither been explored nor handled so far.

Results: We present the Miscoto tool to facilitate the selection of a community optimizing a desired function in a microbiome by reporting several possibilities which can be then sorted according to biological criteria. Communities are exhaustively identified using logical programming and by combining the non-compartmentalized and the compartmentalized frameworks. The benchmarking of 4.9 million metabolic functions associated with the Human Microbiome Project, shows that Miscoto is suited to screen and classify metabolic producibility in terms of feasibility, functional redundancy and cooperation processes involved. As an illustration of a host-microbial system, screening the Recon 2.2 human metabolism highlights the role of different consortia within a family of 773 intestinal bacteria.

Miscoto source code, instructions for use and examples are available at: https://github.com/cfrioux/miscoto.},
}

According to the Human Microbiome Project (HMP), a healthy human body contains ten times more microbes than human cells. Microbial communities colonize different organs of the body, playing fundamental roles both in human health and disease. Despite the vast scientific knowledge of the role of microbial communities in a living body, little is known at present about microbial changes occurring after death, thus leading many authors to investigate the composition of the thanatomicrobiome and its potential applications in the forensic field. The aim of the following review is to provide a general overview of the advances of postmortem microbiology research, mainly focusing on the role of microbiological investigations carried out on internal organs and fluids. To this end, a total of 19 studies have been sistematically reviewed, each one chosen according to specific inclusion/exclusion criteria. The selected studies assess the contribution of contamination, postmortem transmigration and agonal spread to microbial isolation from dead body samples, and shed light on the role of postmortem microbiological investigations in several forensic fields, such as cause of death or PMI determination.

@article {pmid30419494,
year = {2018},
author = {Ventura Spagnolo, E and Stassi, C and Mondello, C and Zerbo, S and Milone, L and Argo, A},
title = {Forensic microbiology applications: A systematic review.},
journal = {Legal medicine (Tokyo, Japan)},
volume = {36},
number = {},
pages = {73-80},
doi = {10.1016/j.legalmed.2018.11.002},
pmid = {30419494},
issn = {1873-4162},
abstract = {According to the Human Microbiome Project (HMP), a healthy human body contains ten times more microbes than human cells. Microbial communities colonize different organs of the body, playing fundamental roles both in human health and disease. Despite the vast scientific knowledge of the role of microbial communities in a living body, little is known at present about microbial changes occurring after death, thus leading many authors to investigate the composition of the thanatomicrobiome and its potential applications in the forensic field. The aim of the following review is to provide a general overview of the advances of postmortem microbiology research, mainly focusing on the role of microbiological investigations carried out on internal organs and fluids. To this end, a total of 19 studies have been sistematically reviewed, each one chosen according to specific inclusion/exclusion criteria. The selected studies assess the contribution of contamination, postmortem transmigration and agonal spread to microbial isolation from dead body samples, and shed light on the role of postmortem microbiological investigations in several forensic fields, such as cause of death or PMI determination.},
}

RevDate: 2018-11-07

Ojo-Okunola A, Nicol M, E du Toit (2018)

Human Breast Milk Bacteriome in Health and Disease.

Nutrients, 10(11): pii:nu10111643.

It is well-known that, beyond nutritional components, human breast milk (HBM) contains a wide variety of non-nutritive bio-factors perfectly suited for the growing infant. In the pre-2000 era, HBM was considered sterile and devoid of micro-organisms. Though HBM was not included as part of the human microbiome project launched in 2007, great strides have been made in studying the bacterial diversity of HBM in both a healthy state and diseased state, and in understanding their role in infant health. HBM provides a vast array of beneficial micro-organisms that play a key role in colonizing the infant's mucosal system, including that of the gut. They also have a role in priming the infant's immune system and supporting its maturation. In this review, we provide an in-depth and updated insight into the immunomodulatory, metabolic, and anti-infective role of HBM bacteriome (bacterial community) and its effect on infant health. We also provide key information from the literature by exploring the possible origin of microbial communities in HBM, the bacterial diversity in this niche and the determinants influencing the HBM bacteriome. Lastly, we investigate the role of the HBM bacteriome in maternal infectious disease (human immunodeficiency virus (HIV) and mastitis)), and cancer. Key gaps in HBM bacterial research are also identified.

@article {pmid30400268,
year = {2018},
author = {Ojo-Okunola, A and Nicol, M and du Toit, E},
title = {Human Breast Milk Bacteriome in Health and Disease.},
journal = {Nutrients},
volume = {10},
number = {11},
pages = {},
doi = {10.3390/nu10111643},
pmid = {30400268},
issn = {2072-6643},
support = {U54HG009824//NIH Office of the Director/ ; 1U01AI110466-01A1//H3Africa U01 AWARD FROM THE NATIONAL INSTITUTES OF HEALTH OF THE USA/ ; OPP1017641; OPP1017579//Bill and Melinda Gates Foundation/ ; },
abstract = {It is well-known that, beyond nutritional components, human breast milk (HBM) contains a wide variety of non-nutritive bio-factors perfectly suited for the growing infant. In the pre-2000 era, HBM was considered sterile and devoid of micro-organisms. Though HBM was not included as part of the human microbiome project launched in 2007, great strides have been made in studying the bacterial diversity of HBM in both a healthy state and diseased state, and in understanding their role in infant health. HBM provides a vast array of beneficial micro-organisms that play a key role in colonizing the infant's mucosal system, including that of the gut. They also have a role in priming the infant's immune system and supporting its maturation. In this review, we provide an in-depth and updated insight into the immunomodulatory, metabolic, and anti-infective role of HBM bacteriome (bacterial community) and its effect on infant health. We also provide key information from the literature by exploring the possible origin of microbial communities in HBM, the bacterial diversity in this niche and the determinants influencing the HBM bacteriome. Lastly, we investigate the role of the HBM bacteriome in maternal infectious disease (human immunodeficiency virus (HIV) and mastitis)), and cancer. Key gaps in HBM bacterial research are also identified.},
}

I extend the classic SAR, which has achieved status of ecological law and plays a critical role in global biodiversity and biogeography analyses, to general DAR (diversity-area relationship). The extension was aimed to remedy a serious application limitation of the traditional SAR that only addressed one aspect of biodiversity scaling-species richness scaling over space, but ignoring species abundance information. The extension was further inspired by a recent consensus that Hill numbers offer the most appropriate measures for alpha-diversity and multiplicative beta-diversity. In particular, Hill numbers are essentially a series of Renyi's entropy values weighted differently along the rare-common-dominant spectrum of species abundance distribution and are in the units of effective number of species (or species equivalents such as OTUs). I therefore postulate that Hill numbers should follow the same or similar law of the traditional SAR. I test the postulation with the American gut microbiome project (AGP) dataset of 1,473 healthy North American individuals. I further propose three new concepts and develop their statistical estimation formulae based on the new DAR extension, including: (i) DAR profile-z-q relationship (DAR scaling parameter z at different diversity order q), (ii) PDO (pair-wise diversity overlap) profile-g-q relationship (PDO parameter g at order q, and (iii) MAD (maximal accrual diversity: Dmax) profile-Dmax-q. While the classic SAR is a special case of our new DAR profile, the PDO and MAD profiles offer novel tools for analyzing biodiversity (including alpha-diversity and beta-diversity) and biogeography over space.

@article {pmid30397444,
year = {2018},
author = {Ma, ZS},
title = {DAR (diversity-area relationship): Extending classic SAR (species-area relationship) for biodiversity and biogeography analyses.},
journal = {Ecology and evolution},
volume = {8},
number = {20},
pages = {10023-10038},
doi = {10.1002/ece3.4425},
pmid = {30397444},
issn = {2045-7758},
abstract = {I extend the classic SAR, which has achieved status of ecological law and plays a critical role in global biodiversity and biogeography analyses, to general DAR (diversity-area relationship). The extension was aimed to remedy a serious application limitation of the traditional SAR that only addressed one aspect of biodiversity scaling-species richness scaling over space, but ignoring species abundance information. The extension was further inspired by a recent consensus that Hill numbers offer the most appropriate measures for alpha-diversity and multiplicative beta-diversity. In particular, Hill numbers are essentially a series of Renyi's entropy values weighted differently along the rare-common-dominant spectrum of species abundance distribution and are in the units of effective number of species (or species equivalents such as OTUs). I therefore postulate that Hill numbers should follow the same or similar law of the traditional SAR. I test the postulation with the American gut microbiome project (AGP) dataset of 1,473 healthy North American individuals. I further propose three new concepts and develop their statistical estimation formulae based on the new DAR extension, including: (i) DAR profile-z-q relationship (DAR scaling parameter z at different diversity order q), (ii) PDO (pair-wise diversity overlap) profile-g-q relationship (PDO parameter g at order q, and (iii) MAD (maximal accrual diversity: Dmax) profile-Dmax-q. While the classic SAR is a special case of our new DAR profile, the PDO and MAD profiles offer novel tools for analyzing biodiversity (including alpha-diversity and beta-diversity) and biogeography over space.},
}

BACKGROUND: Human Microbiome Project reveals the significant mutualistic influence between human body and microbes living in it. Such an influence lead to an interesting phenomenon that many noninfectious diseases are closely associated with diverse microbes. However, the identification of microbe-noninfectious disease associations (MDAs) is still a challenging task, because of both the high cost and the limitation of microbe cultivation. Thus, there is a need to develop fast approaches to screen potential MDAs. The growing number of validated MDAs enables us to meet the demand in a new insight. Computational approaches, especially machine learning, are promising to predict MDA candidates rapidly among a large number of microbe-disease pairs with the advantage of no limitation on microbe cultivation. Nevertheless, a few computational efforts at predicting MDAs are made so far.

RESULTS: In this paper, grouping a set of MDAs into a binary MDA matrix, we propose a novel predictive approach (BMCMDA) based on Binary Matrix Completion to predict potential MDAs. The proposed BMCMDA assumes that the incomplete observed MDA matrix is the summation of a latent parameterizing matrix and a noising matrix. It also assumes that the independently occurring subscripts of observed entries in the MDA matrix follows a binomial model. Adopting a standard mean-zero Gaussian distribution for the nosing matrix, we model the relationship between the parameterizing matrix and the MDA matrix under the observed microbe-disease pairs as a probit regression. With the recovered parameterizing matrix, BMCMDA deduces how likely a microbe would be associated with a particular disease. In the experiment under leave-one-out cross-validation, it exhibits the inspiring performance (AUC = 0.906, AUPR =0.526) and demonstrates its superiority by ~ 7% and ~ 5% improvements in terms of AUC and AUPR respectively in the comparison with the pioneering approach KATZHMDA.

CONCLUSIONS: Our BMCMDA provides an effective approach for predicting MDAs and can be also extended to other similar predicting tasks of binary relationship (e.g. protein-protein interaction, drug-target interaction).

@article {pmid30367598,
year = {2018},
author = {Shi, JY and Huang, H and Zhang, YN and Cao, JB and Yiu, SM},
title = {BMCMDA: a novel model for predicting human microbe-disease associations via binary matrix completion.},
journal = {BMC bioinformatics},
volume = {19},
number = {Suppl 9},
pages = {281},
doi = {10.1186/s12859-018-2274-3},
pmid = {30367598},
issn = {1471-2105},
abstract = {BACKGROUND: Human Microbiome Project reveals the significant mutualistic influence between human body and microbes living in it. Such an influence lead to an interesting phenomenon that many noninfectious diseases are closely associated with diverse microbes. However, the identification of microbe-noninfectious disease associations (MDAs) is still a challenging task, because of both the high cost and the limitation of microbe cultivation. Thus, there is a need to develop fast approaches to screen potential MDAs. The growing number of validated MDAs enables us to meet the demand in a new insight. Computational approaches, especially machine learning, are promising to predict MDA candidates rapidly among a large number of microbe-disease pairs with the advantage of no limitation on microbe cultivation. Nevertheless, a few computational efforts at predicting MDAs are made so far.

RESULTS: In this paper, grouping a set of MDAs into a binary MDA matrix, we propose a novel predictive approach (BMCMDA) based on Binary Matrix Completion to predict potential MDAs. The proposed BMCMDA assumes that the incomplete observed MDA matrix is the summation of a latent parameterizing matrix and a noising matrix. It also assumes that the independently occurring subscripts of observed entries in the MDA matrix follows a binomial model. Adopting a standard mean-zero Gaussian distribution for the nosing matrix, we model the relationship between the parameterizing matrix and the MDA matrix under the observed microbe-disease pairs as a probit regression. With the recovered parameterizing matrix, BMCMDA deduces how likely a microbe would be associated with a particular disease. In the experiment under leave-one-out cross-validation, it exhibits the inspiring performance (AUC = 0.906, AUPR =0.526) and demonstrates its superiority by ~ 7% and ~ 5% improvements in terms of AUC and AUPR respectively in the comparison with the pioneering approach KATZHMDA.

CONCLUSIONS: Our BMCMDA provides an effective approach for predicting MDAs and can be also extended to other similar predicting tasks of binary relationship (e.g. protein-protein interaction, drug-target interaction).},
}

RevDate: 2018-11-14

Chaudhari NM, Gautam A, Gupta VK, et al (2018)

PanGFR-HM: A Dynamic Web Resource for Pan-Genomic and Functional Profiling of Human Microbiome With Comparative Features.

Frontiers in microbiology, 9:2322.

The conglomerate of microorganisms inhabiting various body-sites of human, known as the human microbiome, is one of the key determinants of human health and disease. Comprehensive pan-genomic and functional analysis approach for human microbiome components can enrich our understanding about impact of microbiome on human health. By utilizing this approach we developed PanGFR-HM (http://www.bioinfo.iicb.res.in/pangfr-hm/) - a novel dynamic web-resource that integrates genomic and functional characteristics of 1293 complete microbial genomes available from Human Microbiome Project. The resource allows users to explore genomic/functional diversity and genome-based phylogenetic relationships between human associated microbial genomes, not provided by any other resource. The key features implemented here include pan-genome and functional analysis of organisms based on taxonomy or body-site, and comparative analysis between groups of organisms. The first feature can also identify probable gene-loss events and significantly over/under represented KEGG/COG categories within pan-genome. The unique second feature can perform comparative genomic, functional and pathways analysis between 4 groups of microbes. The dynamic nature of this resource enables users to define parameters for orthologous clustering and to select any set of organisms for analysis. As an application for comparative feature of PanGFR-HM, we performed a comparative analysis with 67 Lactobacillus genomes isolated from human gut, oral cavity and urogenital tract, and therefore characterized the body-site specific genes, enzymes and pathways. Altogether, PanGFR-HM, being unique in its content and functionality, is expected to provide a platform for microbiome-based comparative functional and evolutionary genomics.

@article {pmid30349509,
year = {2018},
author = {Chaudhari, NM and Gautam, A and Gupta, VK and Kaur, G and Dutta, C and Paul, S},
title = {PanGFR-HM: A Dynamic Web Resource for Pan-Genomic and Functional Profiling of Human Microbiome With Comparative Features.},
journal = {Frontiers in microbiology},
volume = {9},
number = {},
pages = {2322},
doi = {10.3389/fmicb.2018.02322},
pmid = {30349509},
issn = {1664-302X},
abstract = {The conglomerate of microorganisms inhabiting various body-sites of human, known as the human microbiome, is one of the key determinants of human health and disease. Comprehensive pan-genomic and functional analysis approach for human microbiome components can enrich our understanding about impact of microbiome on human health. By utilizing this approach we developed PanGFR-HM (http://www.bioinfo.iicb.res.in/pangfr-hm/) - a novel dynamic web-resource that integrates genomic and functional characteristics of 1293 complete microbial genomes available from Human Microbiome Project. The resource allows users to explore genomic/functional diversity and genome-based phylogenetic relationships between human associated microbial genomes, not provided by any other resource. The key features implemented here include pan-genome and functional analysis of organisms based on taxonomy or body-site, and comparative analysis between groups of organisms. The first feature can also identify probable gene-loss events and significantly over/under represented KEGG/COG categories within pan-genome. The unique second feature can perform comparative genomic, functional and pathways analysis between 4 groups of microbes. The dynamic nature of this resource enables users to define parameters for orthologous clustering and to select any set of organisms for analysis. As an application for comparative feature of PanGFR-HM, we performed a comparative analysis with 67 Lactobacillus genomes isolated from human gut, oral cavity and urogenital tract, and therefore characterized the body-site specific genes, enzymes and pathways. Altogether, PanGFR-HM, being unique in its content and functionality, is expected to provide a platform for microbiome-based comparative functional and evolutionary genomics.},
}

RevDate: 2018-11-14

Chen Z, Yeoh YK, Hui M, et al (2018)

Diversity of macaque microbiota compared to the human counterparts.

Scientific reports, 8(1):15573 pii:10.1038/s41598-018-33950-6.

Studies on the microbial communities in non-human primate hosts provide unique insights in both evolution and function of microbes related to human health and diseases. Using 16S rRNA gene amplicon profiling, we examined the oral, anal and vaginal microbiota in a group of non-captive rhesus macaques (N = 116) and compared the compositions with the healthy communities from Human Microbiome Project. The macaque microbiota was dominated by Bacteroidetes, Firmicutes and Proteobacteria; however, there were marked differences in phylotypes enriched across body sites indicative of strong niche specialization. Compared to human gut microbiota where Bacteroides predominately enriched, the surveyed macaque anal community exhibited increased abundance of Prevotella. In contrast to the conserved human vaginal microbiota extremely dominated by Lactobacillus, the macaque vaginal microbial composition was highly diverse while lactobacilli were rare. A constant decrease of the vaginal microbiota diversity was observed among macaque samples from juvenile, adult without tubectomy, and adult with tubectomy, with the most notable distinction being the enrichment of Halomonas in juvenile and Saccharofermentans in contracepted adults. Both macaque and human oral microbiota were colonized with three most common oral bacterial genera: Streptococcus, Haemophilus and Veillonella, and shared relatively conserved communities to each other. A number of bacteria related to human pathogens were consistently detected in macaques. The findings delineate the range of structure and diversity of microbial communities in a wild macaque population, and enable the application of macaque as an animal model for future characterization of microbes in transmission, genomics and function.

@article {pmid30349024,
year = {2018},
author = {Chen, Z and Yeoh, YK and Hui, M and Wong, PY and Chan, MCW and Ip, M and Yu, J and Burk, RD and Chan, FKL and Chan, PKS},
title = {Diversity of macaque microbiota compared to the human counterparts.},
journal = {Scientific reports},
volume = {8},
number = {1},
pages = {15573},
doi = {10.1038/s41598-018-33950-6},
pmid = {30349024},
issn = {2045-2322},
abstract = {Studies on the microbial communities in non-human primate hosts provide unique insights in both evolution and function of microbes related to human health and diseases. Using 16S rRNA gene amplicon profiling, we examined the oral, anal and vaginal microbiota in a group of non-captive rhesus macaques (N = 116) and compared the compositions with the healthy communities from Human Microbiome Project. The macaque microbiota was dominated by Bacteroidetes, Firmicutes and Proteobacteria; however, there were marked differences in phylotypes enriched across body sites indicative of strong niche specialization. Compared to human gut microbiota where Bacteroides predominately enriched, the surveyed macaque anal community exhibited increased abundance of Prevotella. In contrast to the conserved human vaginal microbiota extremely dominated by Lactobacillus, the macaque vaginal microbial composition was highly diverse while lactobacilli were rare. A constant decrease of the vaginal microbiota diversity was observed among macaque samples from juvenile, adult without tubectomy, and adult with tubectomy, with the most notable distinction being the enrichment of Halomonas in juvenile and Saccharofermentans in contracepted adults. Both macaque and human oral microbiota were colonized with three most common oral bacterial genera: Streptococcus, Haemophilus and Veillonella, and shared relatively conserved communities to each other. A number of bacteria related to human pathogens were consistently detected in macaques. The findings delineate the range of structure and diversity of microbial communities in a wild macaque population, and enable the application of macaque as an animal model for future characterization of microbes in transmission, genomics and function.},
}

RevDate: 2018-11-14

Wyman SK, Avila-Herrera A, Nayfach S, et al (2018)

A most wanted list of conserved microbial protein families with no known domains.

PloS one, 13(10):e0205749 pii:PONE-D-18-08043.

The number and proportion of genes with no known function are growing rapidly. To quantify this phenomenon and provide criteria for prioritizing genes for functional characterization, we developed a bioinformatics pipeline that identifies robustly defined protein families with no annotated domains, ranks these with respect to phylogenetic breadth, and identifies them in metagenomics data. We applied this approach to 271 965 protein families from the SFams database and discovered many with no functional annotation, including >118 000 families lacking any known protein domain. From these, we prioritized 6 668 conserved protein families with at least three sequences from organisms in at least two distinct classes. These Function Unknown Families (FUnkFams) are present in Tara Oceans Expedition and Human Microbiome Project metagenomes, with distributions associated with sampling environment. Our findings highlight the extent of functional novelty in sequence databases and establish an approach for creating a "most wanted" list of genes to prioritize for further characterization.

@article {pmid30332487,
year = {2018},
author = {Wyman, SK and Avila-Herrera, A and Nayfach, S and Pollard, KS},
title = {A most wanted list of conserved microbial protein families with no known domains.},
journal = {PloS one},
volume = {13},
number = {10},
pages = {e0205749},
doi = {10.1371/journal.pone.0205749},
pmid = {30332487},
issn = {1932-6203},
abstract = {The number and proportion of genes with no known function are growing rapidly. To quantify this phenomenon and provide criteria for prioritizing genes for functional characterization, we developed a bioinformatics pipeline that identifies robustly defined protein families with no annotated domains, ranks these with respect to phylogenetic breadth, and identifies them in metagenomics data. We applied this approach to 271 965 protein families from the SFams database and discovered many with no functional annotation, including >118 000 families lacking any known protein domain. From these, we prioritized 6 668 conserved protein families with at least three sequences from organisms in at least two distinct classes. These Function Unknown Families (FUnkFams) are present in Tara Oceans Expedition and Human Microbiome Project metagenomes, with distributions associated with sampling environment. Our findings highlight the extent of functional novelty in sequence databases and establish an approach for creating a "most wanted" list of genes to prioritize for further characterization.},
}

RevDate: 2018-11-16

Gonzalez A, Navas-Molina JA, Kosciolek T, et al (2018)

Qiita: rapid, web-enabled microbiome meta-analysis.

Nature methods, 15(10):796-798.

Multi-omic insights into microbiome function and composition typically advance one study at a time. However, in order for relationships across studies to be fully understood, data must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome-comparison platform, which we demonstrate with Human Microbiome Project and Integrative Human Microbiome Project (iHMP) data.

@article {pmid30275573,
year = {2018},
author = {Gonzalez, A and Navas-Molina, JA and Kosciolek, T and McDonald, D and Vázquez-Baeza, Y and Ackermann, G and DeReus, J and Janssen, S and Swafford, AD and Orchanian, SB and Sanders, JG and Shorenstein, J and Holste, H and Petrus, S and Robbins-Pianka, A and Brislawn, CJ and Wang, M and Rideout, JR and Bolyen, E and Dillon, M and Caporaso, JG and Dorrestein, PC and Knight, R},
title = {Qiita: rapid, web-enabled microbiome meta-analysis.},
journal = {Nature methods},
volume = {15},
number = {10},
pages = {796-798},
doi = {10.1038/s41592-018-0141-9},
pmid = {30275573},
issn = {1548-7105},
support = {P01 DK078669/DK/NIDDK NIH HHS/United States ; R01 HG004872/HG/NHGRI NIH HHS/United States ; R01 HL140976/HL/NHLBI NIH HHS/United States ; R01 MD011389/MD/NIMHD NIH HHS/United States ; },
abstract = {Multi-omic insights into microbiome function and composition typically advance one study at a time. However, in order for relationships across studies to be fully understood, data must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome-comparison platform, which we demonstrate with Human Microbiome Project and Integrative Human Microbiome Project (iHMP) data.},
}

RevDate: 2018-10-26CmpDate: 2018-10-26

Aziz RK, Hegazy SM, Yasser R, et al (2018)

Drug pharmacomicrobiomics and toxicomicrobiomics: from scattered reports to systematic studies of drug-microbiome interactions.

Expert opinion on drug metabolism & toxicology, 14(10):1043-1055.

INTRODUCTION: Pharmacomicrobiomics and toxicomicrobiomics study how variations within the human microbiome (the combination of human-associated microbial communities and their genomes) affect drug disposition, action, and toxicity. These emerging fields, interconnecting microbiology, bioinformatics, systems pharmacology, and toxicology, complement pharmacogenomics and toxicogenomics, expanding the scope of precision medicine. Areas covered: This article reviews some of the most recently reported pharmacomicrobiomic and toxicomicrobiomic interactions. Examples include the impact of the human gut microbiota on cardiovascular drugs, natural products, and chemotherapeutic agents, including immune checkpoint inhibitors. Although the gut microbiota has been the most extensively studied, some key drug-microbiome interactions involve vaginal, intratumoral, and environmental bacteria, and are briefly discussed here. Additionally, computational resources, moving the field from cataloging to predicting interactions, are introduced. Expert opinion: The rapid pace of discovery triggered by the Human Microbiome Project is moving pharmacomicrobiomic research from scattered observations to systematic studies focusing on screening microbiome variants against different drug classes. Better representation of all human populations will improve such studies by avoiding sampling bias, and the integration of multiomic studies with designed experiments will allow establishing causation. In the near future, pharmacomicrobiomic testing is expected to be a key step in screening novel drugs and designing precision therapeutics.

Linking gut microbiota, metabolic syndrome and economic status based on a population-level analysis.

Microbiome, 6(1):172 pii:10.1186/s40168-018-0557-6.

BACKGROUND: The metabolic syndrome (MetS) epidemic is associated with economic development, lifestyle transition and dysbiosis of gut microbiota, but these associations are rarely studied at the population scale. Here, we utilised the Guangdong Gut Microbiome Project (GGMP), the largest Eastern population-based gut microbiome dataset covering individuals with different economic statuses, to investigate the relationships between the gut microbiome and host physiology, diet, geography, physical activity and socioeconomic status.

RESULTS: At the population level, 529 OTUs were significantly associated with MetS. OTUs from Proteobacteria and Firmicutes (other than Ruminococcaceae) were mainly positively associated with MetS, whereas those from Bacteroidetes and Ruminococcaceae were negatively associated with MetS. Two hundred fourteen OTUs were significantly associated with host economic status (140 positive and 74 negative associations), and 157 of these OTUs were also MetS associated. A microbial MetS index was formulated to represent the overall gut dysbiosis of MetS. The values of this index were significantly higher in MetS subjects regardless of their economic status or geographical location. The index values did not increase with increasing personal economic status, although the prevalence of MetS was significantly higher in people of higher economic status. With increased economic status, the study population tended to consume more fruits and vegetables and fewer grains, whereas meat consumption was unchanged. Sedentary time was significantly and positively associated with higher economic status. The MetS index showed an additive effect with sedentary lifestyle, as the prevalence of MetS in individuals with high MetS index values and unhealthy lifestyles was significantly higher than that in the rest of the population.

CONCLUSIONS: The gut microbiome is associated with MetS and economic status. A prolonged sedentary lifestyle, rather than Westernised dietary patterns, was the most notable lifestyle change in our Eastern population along with economic development. Moreover, gut dysbiosis and a Western lifestyle had an additive effect on increasing MetS prevalence.

RESULTS: At the population level, 529 OTUs were significantly associated with MetS. OTUs from Proteobacteria and Firmicutes (other than Ruminococcaceae) were mainly positively associated with MetS, whereas those from Bacteroidetes and Ruminococcaceae were negatively associated with MetS. Two hundred fourteen OTUs were significantly associated with host economic status (140 positive and 74 negative associations), and 157 of these OTUs were also MetS associated. A microbial MetS index was formulated to represent the overall gut dysbiosis of MetS. The values of this index were significantly higher in MetS subjects regardless of their economic status or geographical location. The index values did not increase with increasing personal economic status, although the prevalence of MetS was significantly higher in people of higher economic status. With increased economic status, the study population tended to consume more fruits and vegetables and fewer grains, whereas meat consumption was unchanged. Sedentary time was significantly and positively associated with higher economic status. The MetS index showed an additive effect with sedentary lifestyle, as the prevalence of MetS in individuals with high MetS index values and unhealthy lifestyles was significantly higher than that in the rest of the population.

CONCLUSIONS: The gut microbiome is associated with MetS and economic status. A prolonged sedentary lifestyle, rather than Westernised dietary patterns, was the most notable lifestyle change in our Eastern population along with economic development. Moreover, gut dysbiosis and a Western lifestyle had an additive effect on increasing MetS prevalence.},
}

RevDate: 2018-11-22

Little MS, Ervin SM, Walton WG, et al (2018)

Active site flexibility revealed in crystal structures of Parabacteroides merdae β-glucuronidase from the human gut microbiome.

Protein science : a publication of the Protein Society, 27(12):2010-2022.

β-Glucuronidase (GUS) enzymes in the gastrointestinal tract are involved in maintaining mammalian-microbial symbiosis and can play key roles in drug efficacy and toxicity. Parabacteroides merdae GUS was identified as an abundant mini-Loop 2 (mL2) type GUS enzyme in the Human Microbiome Project gut metagenomic database. Here, we report the crystal structure of P. merdae GUS and highlight the differences between this enzyme and extant structures of gut microbial GUS proteins. We find that P. merdae GUS exhibits a distinct tetrameric quaternary structure and that the mL2 motif traces a unique path within the active site, which also includes two arginines distinctive to this GUS. We observe two states of the P. merdae GUS active site; a loop repositions itself by more than 50 Å to place a functionally-relevant residue into the enzyme's catalytic site. Finally, we find that P. merdae GUS is able to bind to homo and heteropolymers of the polysaccharide alginic acid. Together, these data broaden our understanding of the structural and functional diversity in the GUS family of enzymes present in the human gut microbiome and point to specialization as an important feature of microbial GUS orthologs.

@article {pmid30230652,
year = {2018},
author = {Little, MS and Ervin, SM and Walton, WG and Tripathy, A and Xu, Y and Liu, J and Redinbo, MR},
title = {Active site flexibility revealed in crystal structures of Parabacteroides merdae β-glucuronidase from the human gut microbiome.},
journal = {Protein science : a publication of the Protein Society},
volume = {27},
number = {12},
pages = {2010-2022},
doi = {10.1002/pro.3507},
pmid = {30230652},
issn = {1469-896X},
support = {CA098468CA207416//National Institutes of Health/ ; DGS-1650116//National Science Foundation/ ; },
abstract = {β-Glucuronidase (GUS) enzymes in the gastrointestinal tract are involved in maintaining mammalian-microbial symbiosis and can play key roles in drug efficacy and toxicity. Parabacteroides merdae GUS was identified as an abundant mini-Loop 2 (mL2) type GUS enzyme in the Human Microbiome Project gut metagenomic database. Here, we report the crystal structure of P. merdae GUS and highlight the differences between this enzyme and extant structures of gut microbial GUS proteins. We find that P. merdae GUS exhibits a distinct tetrameric quaternary structure and that the mL2 motif traces a unique path within the active site, which also includes two arginines distinctive to this GUS. We observe two states of the P. merdae GUS active site; a loop repositions itself by more than 50 Å to place a functionally-relevant residue into the enzyme's catalytic site. Finally, we find that P. merdae GUS is able to bind to homo and heteropolymers of the polysaccharide alginic acid. Together, these data broaden our understanding of the structural and functional diversity in the GUS family of enzymes present in the human gut microbiome and point to specialization as an important feature of microbial GUS orthologs.},
}

RevDate: 2018-11-14

Xia Y, J Sun (2017)

Hypothesis Testing and Statistical Analysis of Microbiome.

Genes & diseases, 4(3):138-148.

After the initiation of Human Microbiome Project in 2008, various biostatistic and bioinformatic tools for data analysis and computational methods have been developed and applied to microbiome studies. In this review and perspective, we discuss the research and statistical hypotheses in gut microbiome studies, focusing on mechanistic concepts that underlie the complex relationships among host, microbiome, and environment. We review the current available statistic tools and highlight recent progress of newly developed statistical methods and models. Given the current challenges and limitations in biostatistic approaches and tools, we discuss the future direction in developing statistical methods and models for the microbiome studies.

@article {pmid30197908,
year = {2017},
author = {Xia, Y and Sun, J},
title = {Hypothesis Testing and Statistical Analysis of Microbiome.},
journal = {Genes & diseases},
volume = {4},
number = {3},
pages = {138-148},
doi = {10.1016/j.gendis.2017.06.001},
pmid = {30197908},
issn = {2352-4820},
support = {R01 DK105118/DK/NIDDK NIH HHS/United States ; R01 DK114126/DK/NIDDK NIH HHS/United States ; },
abstract = {After the initiation of Human Microbiome Project in 2008, various biostatistic and bioinformatic tools for data analysis and computational methods have been developed and applied to microbiome studies. In this review and perspective, we discuss the research and statistical hypotheses in gut microbiome studies, focusing on mechanistic concepts that underlie the complex relationships among host, microbiome, and environment. We review the current available statistic tools and highlight recent progress of newly developed statistical methods and models. Given the current challenges and limitations in biostatistic approaches and tools, we discuss the future direction in developing statistical methods and models for the microbiome studies.},
}

BACKGROUND: Fetal growth restriction, pre-eclampsia, and pre-term birth are major adverse pregnancy outcomes. These complications are considerable contributors to fetal/maternal morbidity and mortality worldwide. A significant proportion of these cases are thought to be due to dysfunction of the placenta. However, the underlying mechanisms of placental dysfunction are unclear. The aim of the present study was to investigate whether adverse pregnancy outcomes are associated with evidence of placental eukaryotic infection.

RESULTS: We modified the 18S Illumina Amplicon Protocol of the Earth Microbiome Project and made it capable of detecting just a single spiked-in genome copy of Plasmodium falciparum, Saccharomyces cerevisiae, or Toxoplasma gondii among more than 70,000 human cells. Using this method, we were unable to detect eukaryotic pathogens in placental biopsies in instances of adverse pregnancy outcome (n = 199) or in healthy controls (n = 99).

CONCLUSIONS: Eukaryotic infection of the placenta is not an underlying cause of the aforementioned pregnancy complications. Possible clinical applications for this non-targeted, yet extremely sensitive, eukaryotic screening method are manifest.

@article {pmid30172254,
year = {2018},
author = {Lager, S and de Goffau, MC and Sovio, U and Peacock, SJ and Parkhill, J and Charnock-Jones, DS and Smith, GCS},
title = {Detecting eukaryotic microbiota with single-cell sensitivity in human tissue.},
journal = {Microbiome},
volume = {6},
number = {1},
pages = {151},
doi = {10.1186/s40168-018-0529-x},
pmid = {30172254},
issn = {2049-2618},
support = {G1100221//Medical Research Council/United Kingdom ; },
abstract = {BACKGROUND: Fetal growth restriction, pre-eclampsia, and pre-term birth are major adverse pregnancy outcomes. These complications are considerable contributors to fetal/maternal morbidity and mortality worldwide. A significant proportion of these cases are thought to be due to dysfunction of the placenta. However, the underlying mechanisms of placental dysfunction are unclear. The aim of the present study was to investigate whether adverse pregnancy outcomes are associated with evidence of placental eukaryotic infection.

RESULTS: We modified the 18S Illumina Amplicon Protocol of the Earth Microbiome Project and made it capable of detecting just a single spiked-in genome copy of Plasmodium falciparum, Saccharomyces cerevisiae, or Toxoplasma gondii among more than 70,000 human cells. Using this method, we were unable to detect eukaryotic pathogens in placental biopsies in instances of adverse pregnancy outcome (n = 199) or in healthy controls (n = 99).

CONCLUSIONS: Eukaryotic infection of the placenta is not an underlying cause of the aforementioned pregnancy complications. Possible clinical applications for this non-targeted, yet extremely sensitive, eukaryotic screening method are manifest.},
}

SAR (species area relationship) is a classic ecological theory that has been extensively investigated and applied in the studies of global biogeography and biodiversity conservation in macro-ecology. It has also found important applications in microbial ecology in recent years thanks to the breakthroughs in metagenomic sequencing technology. Nevertheless, SAR has a serious limitation for practical applications-ignoring the species abundance and treating all species as equally abundant. This study aims to explore the biogeography discoveries of human microbiome over 18 sites of 5 major microbiome habitats, establish the baseline DAR (diversity-area scaling relationship) parameters, and perform comparisons with the classic SAR. The extension from SAR to DAR by adopting the Hill numbers as diversity measures not only overcomes the previously mentioned flaw of SAR but also allows for obtaining a series of important findings on the human microbiome biodiversity and biogeography. Specifically, two types of DAR models were built, the traditional power law (PL) and power law with exponential cutoff (PLEC), using comprehensive datasets from the HMP (human microbiome project). Furthermore, the biogeography "maps" for 18 human microbiome sites using their DAR profiles for assessing and predicting the diversity scaling across individuals, PDO profiles (pair-wise diversity overlap) for measuring diversity overlap (similarity), and MAD profile (for predicting the maximal accrual diversity in a population) were sketched out. The baseline biogeography maps for the healthy human microbiome diversity can offer guidelines for conserving human microbiome diversity and investigating the health implications of the human microbiome diversity and heterogeneity.

@article {pmid30155556,
year = {2018},
author = {Ma, ZS},
title = {Sketching the Human Microbiome Biogeography with DAR (Diversity-Area Relationship) Profiles.},
journal = {Microbial ecology},
volume = {},
number = {},
pages = {},
doi = {10.1007/s00248-018-1245-6},
pmid = {30155556},
issn = {1432-184X},
abstract = {SAR (species area relationship) is a classic ecological theory that has been extensively investigated and applied in the studies of global biogeography and biodiversity conservation in macro-ecology. It has also found important applications in microbial ecology in recent years thanks to the breakthroughs in metagenomic sequencing technology. Nevertheless, SAR has a serious limitation for practical applications-ignoring the species abundance and treating all species as equally abundant. This study aims to explore the biogeography discoveries of human microbiome over 18 sites of 5 major microbiome habitats, establish the baseline DAR (diversity-area scaling relationship) parameters, and perform comparisons with the classic SAR. The extension from SAR to DAR by adopting the Hill numbers as diversity measures not only overcomes the previously mentioned flaw of SAR but also allows for obtaining a series of important findings on the human microbiome biodiversity and biogeography. Specifically, two types of DAR models were built, the traditional power law (PL) and power law with exponential cutoff (PLEC), using comprehensive datasets from the HMP (human microbiome project). Furthermore, the biogeography "maps" for 18 human microbiome sites using their DAR profiles for assessing and predicting the diversity scaling across individuals, PDO profiles (pair-wise diversity overlap) for measuring diversity overlap (similarity), and MAD profile (for predicting the maximal accrual diversity in a population) were sketched out. The baseline biogeography maps for the healthy human microbiome diversity can offer guidelines for conserving human microbiome diversity and investigating the health implications of the human microbiome diversity and heterogeneity.},
}

RevDate: 2018-11-14

Ma Z, Li L, W Li (2018)

Assessing and Interpreting the Within-Body Biogeography of Human Microbiome Diversity.

Frontiers in microbiology, 9:1619.

A human body hosts a relatively independent microbiome including five major regional biomes (i.e., airway, oral, gut, skin, and urogenital). Each of them may possess different regional characteristics with important implications to our health and diseases (i.e., so-termed microbiome associated diseases). Nevertheless, these regional microbiomes are connected with each other through diffusions and migrations. Here, we investigate the within-body (intra-individual) distribution feature of microbiome diversity via diversity area relationship (DAR) modeling, which, to the best of our knowledge, has not been systematically studied previously. We utilized the Hill numbers for measuring alpha and beta-diversities and built 1,200 within-body DAR models with to date the most comprehensive human microbiome datasets of 18 sites from the human microbiome project (HMP) cohort. We established the intra-DAR profile (z-q pattern: the diversity scaling parameter z of the power law (PL) at diversity order q = 0-3), intra-PDO (pair-wise diversity overlap) profile (g-q), and intra-MAD (maximal accrual diversity) profile (Dmax-q) for the within-body biogeography of the human microbiome. These profiles constitute the "maps" of the within-body biogeography, and offer important insights on the within-body distribution of the human microbiome. Furthermore, we investigated the heterogeneity among individuals in their biogeography parameters and found that there is not an "average Joe" that can represent majority of individuals in a cohort or population. For example, we found that most individuals in the HMP cohort have relatively lower maximal accrual diversity (MAD) or in the "long tail" of the so-termed power law distribution. In the meantime, there are a small number of individuals in the cohort who possess disproportionally higher MAD values. These findings may have important implications for personalized medicine of the human microbiome associated diseases in practice, besides their theoretical significance in microbiome research such as establishing the baseline for the conservation of human microbiome.

@article {pmid30131772,
year = {2018},
author = {Ma, Z and Li, L and Li, W},
title = {Assessing and Interpreting the Within-Body Biogeography of Human Microbiome Diversity.},
journal = {Frontiers in microbiology},
volume = {9},
number = {},
pages = {1619},
doi = {10.3389/fmicb.2018.01619},
pmid = {30131772},
issn = {1664-302X},
abstract = {A human body hosts a relatively independent microbiome including five major regional biomes (i.e., airway, oral, gut, skin, and urogenital). Each of them may possess different regional characteristics with important implications to our health and diseases (i.e., so-termed microbiome associated diseases). Nevertheless, these regional microbiomes are connected with each other through diffusions and migrations. Here, we investigate the within-body (intra-individual) distribution feature of microbiome diversity via diversity area relationship (DAR) modeling, which, to the best of our knowledge, has not been systematically studied previously. We utilized the Hill numbers for measuring alpha and beta-diversities and built 1,200 within-body DAR models with to date the most comprehensive human microbiome datasets of 18 sites from the human microbiome project (HMP) cohort. We established the intra-DAR profile (z-q pattern: the diversity scaling parameter z of the power law (PL) at diversity order q = 0-3), intra-PDO (pair-wise diversity overlap) profile (g-q), and intra-MAD (maximal accrual diversity) profile (Dmax-q) for the within-body biogeography of the human microbiome. These profiles constitute the "maps" of the within-body biogeography, and offer important insights on the within-body distribution of the human microbiome. Furthermore, we investigated the heterogeneity among individuals in their biogeography parameters and found that there is not an "average Joe" that can represent majority of individuals in a cohort or population. For example, we found that most individuals in the HMP cohort have relatively lower maximal accrual diversity (MAD) or in the "long tail" of the so-termed power law distribution. In the meantime, there are a small number of individuals in the cohort who possess disproportionally higher MAD values. These findings may have important implications for personalized medicine of the human microbiome associated diseases in practice, besides their theoretical significance in microbiome research such as establishing the baseline for the conservation of human microbiome.},
}

The human microbiome project via application of metagenomic next-generation sequencing techniques has found surprising large and diverse amounts of microbial sequences across different body sites. There is a wave of investigators studying autoimmune related diseases designing from birth case and control studies to elucidate microbial associations and potential direct triggers. Sequencing analysis, considered big data as it typically includes millions of reads, is challenging but particularly demanding and complex is virome profiling due to its lack of pan-viral genomic signature. Impressively thousands of virus complete genomes have been deposited and these high-quality references are core components of virus profiling pipelines and databases. Still it is commonly known that most viral sequences do not map to known viruses. Moreover human viruses, particularly RNA groups, are notoriously heterogeneous due to high mutation rates. Here, we present the related assembling challenges and a series of bioinformatics steps that were applied in the construction of the complete consensus genome of a novel clinical isolate of Coxsackievirus B1. We further demonstrate our effort in calling mutations between prototype Coxsackievirus B1 sequence from GenBank and serial clinical isolate genome grown in cell culture.

@article {pmid30129002,
year = {2018},
author = {Lin, J and Kimura, BY and Oikarinen, S and Nykter, M},
title = {Bioinformatics Assembling and Assessment of Novel Coxsackievirus B1 Genome.},
journal = {Methods in molecular biology (Clifton, N.J.)},
volume = {1838},
number = {},
pages = {261-272},
doi = {10.1007/978-1-4939-8682-8_18},
pmid = {30129002},
issn = {1940-6029},
abstract = {The human microbiome project via application of metagenomic next-generation sequencing techniques has found surprising large and diverse amounts of microbial sequences across different body sites. There is a wave of investigators studying autoimmune related diseases designing from birth case and control studies to elucidate microbial associations and potential direct triggers. Sequencing analysis, considered big data as it typically includes millions of reads, is challenging but particularly demanding and complex is virome profiling due to its lack of pan-viral genomic signature. Impressively thousands of virus complete genomes have been deposited and these high-quality references are core components of virus profiling pipelines and databases. Still it is commonly known that most viral sequences do not map to known viruses. Moreover human viruses, particularly RNA groups, are notoriously heterogeneous due to high mutation rates. Here, we present the related assembling challenges and a series of bioinformatics steps that were applied in the construction of the complete consensus genome of a novel clinical isolate of Coxsackievirus B1. We further demonstrate our effort in calling mutations between prototype Coxsackievirus B1 sequence from GenBank and serial clinical isolate genome grown in cell culture.},
}

RevDate: 2018-08-12

Kroon SJ, Ravel J, WM Huston (2018)

Cervicovaginal microbiota, women's health, and reproductive outcomes.

Fertility and sterility, 110(3):327-336.

The human microbiome project has shown a remarkable diversity of microbial ecology within the human body. The vaginal microbiota is unique in that in many women it is most often dominated by Lactobacillus species. However, in some women it lacks Lactobacillus spp. and is comprised of a wide array of strict and facultative anaerobes, a state that broadly correlates with increased risk for infection, disease, and poor reproductive and obstetric outcomes. Interestingly, the level of protection against infection can also vary by species and strains of Lactobacillus, and some species although dominant are not always optimal. This factors into the risk of contracting sexually transmitted infections and possibly influences the occurrence of resultant adverse reproductive outcomes such as tubal factor infertility. The composition and function of the vaginal microbiota appear to play an important role in pregnancy and fertility treatment outcomes and future research in this field will shed further translational mechanistic understanding onto the interplay of the vaginal microbiota with women's health and reproduction.

@article {pmid30098679,
year = {2018},
author = {Kroon, SJ and Ravel, J and Huston, WM},
title = {Cervicovaginal microbiota, women's health, and reproductive outcomes.},
journal = {Fertility and sterility},
volume = {110},
number = {3},
pages = {327-336},
doi = {10.1016/j.fertnstert.2018.06.036},
pmid = {30098679},
issn = {1556-5653},
abstract = {The human microbiome project has shown a remarkable diversity of microbial ecology within the human body. The vaginal microbiota is unique in that in many women it is most often dominated by Lactobacillus species. However, in some women it lacks Lactobacillus spp. and is comprised of a wide array of strict and facultative anaerobes, a state that broadly correlates with increased risk for infection, disease, and poor reproductive and obstetric outcomes. Interestingly, the level of protection against infection can also vary by species and strains of Lactobacillus, and some species although dominant are not always optimal. This factors into the risk of contracting sexually transmitted infections and possibly influences the occurrence of resultant adverse reproductive outcomes such as tubal factor infertility. The composition and function of the vaginal microbiota appear to play an important role in pregnancy and fertility treatment outcomes and future research in this field will shed further translational mechanistic understanding onto the interplay of the vaginal microbiota with women's health and reproduction.},
}

RevDate: 2018-10-17

Hanssen EN, Liland KH, Gill P, et al (2018)

Optimizing body fluid recognition from microbial taxonomic profiles.

Forensic science international. Genetics, 37:13-20.

In forensics the DNA-profile is used to identify the person who left a biological trace, but information on body fluid can also be essential in the evidence evaluation process. Microbial composition data could potentially be used for body fluid recognition as an improved alternative to the currently used presumptive tests. We have developed a customized workflow for interpretation of bacterial 16S sequence data based on a model composed of Partial Least Squares (PLS) in combination with Linear Discriminant Analysis (LDA). Large data sets from the Human Microbiome Project (HMP) and the American Gut Project (AGP) were used to test different settings in order to optimize performance. From the initial cross-validation of body fluid recognition within the HMP data, the optimal overall accuracy was close to 98%. Sensitivity values for the fecal and oral samples were ≥0.99, followed by the vaginal samples with 0.98 and the skin and nasal samples with 0.96 and 0.81 respectively. Specificity values were high for all 5 categories, mostly >0.99. This optimal performance was achieved by using the following settings: Taxonomic profiles based on operational taxonomic units (OTUs) with 0.98 identity (OTU98), Aitchisons simplex transform with C = 1 pseudo-count and no regularization (r = 1) in the PLS step. Variable selection did not improve the performance further. To test for robustness across sequencing platforms, we also trained the classifier on HMP data and tested on the AGP data set. In this case, the standard OTU based approach showed moderately decline in accuracy. However, by using taxonomic profiles made by direct assignment of reads to a genus, we were able to nearly maintain the high accuracy levels. The optimal combination of settings was still used, except the taxonomic level being genus instead of OTU98. The performance may be improved even further by using higher resolution taxonomic bins.

@article {pmid30071492,
year = {2018},
author = {Hanssen, EN and Liland, KH and Gill, P and Snipen, L},
title = {Optimizing body fluid recognition from microbial taxonomic profiles.},
journal = {Forensic science international. Genetics},
volume = {37},
number = {},
pages = {13-20},
doi = {10.1016/j.fsigen.2018.07.012},
pmid = {30071492},
issn = {1878-0326},
abstract = {In forensics the DNA-profile is used to identify the person who left a biological trace, but information on body fluid can also be essential in the evidence evaluation process. Microbial composition data could potentially be used for body fluid recognition as an improved alternative to the currently used presumptive tests. We have developed a customized workflow for interpretation of bacterial 16S sequence data based on a model composed of Partial Least Squares (PLS) in combination with Linear Discriminant Analysis (LDA). Large data sets from the Human Microbiome Project (HMP) and the American Gut Project (AGP) were used to test different settings in order to optimize performance. From the initial cross-validation of body fluid recognition within the HMP data, the optimal overall accuracy was close to 98%. Sensitivity values for the fecal and oral samples were ≥0.99, followed by the vaginal samples with 0.98 and the skin and nasal samples with 0.96 and 0.81 respectively. Specificity values were high for all 5 categories, mostly >0.99. This optimal performance was achieved by using the following settings: Taxonomic profiles based on operational taxonomic units (OTUs) with 0.98 identity (OTU98), Aitchisons simplex transform with C = 1 pseudo-count and no regularization (r = 1) in the PLS step. Variable selection did not improve the performance further. To test for robustness across sequencing platforms, we also trained the classifier on HMP data and tested on the AGP data set. In this case, the standard OTU based approach showed moderately decline in accuracy. However, by using taxonomic profiles made by direct assignment of reads to a genus, we were able to nearly maintain the high accuracy levels. The optimal combination of settings was still used, except the taxonomic level being genus instead of OTU98. The performance may be improved even further by using higher resolution taxonomic bins.},
}

RevDate: 2018-11-14

Tripathi A, Marotz C, Gonzalez A, et al (2018)

Are microbiome studies ready for hypothesis-driven research?.

Current opinion in microbiology, 44:61-69.

Hypothesis-driven research has led to many scientific advances, but hypotheses cannot be tested in isolation: rather, they require a framework of aggregated scientific knowledge to allow questions to be posed meaningfully. This framework is largely still lacking in microbiome studies, and the only way to create it is by discovery-driven, tool-driven, and standards-driven research projects. Here we illustrate these issues using several such non-hypothesis-driven projects from our own laboratories, including spatial mapping, the American Gut Project, the Earth Microbiome Project (which is an umbrella project integrating many smaller hypothesis-driven projects), and the knowledgebase-driven tools GNPS and Qiita. We argue that an investment of community resources in infrastructure tasks, and in the controls and standards that underpin them, will greatly enhance the investment in hypothesis-driven research programs.

@article {pmid30059804,
year = {2018},
author = {Tripathi, A and Marotz, C and Gonzalez, A and Vázquez-Baeza, Y and Song, SJ and Bouslimani, A and McDonald, D and Zhu, Q and Sanders, JG and Smarr, L and Dorrestein, PC and Knight, R},
title = {Are microbiome studies ready for hypothesis-driven research?.},
journal = {Current opinion in microbiology},
volume = {44},
number = {},
pages = {61-69},
doi = {10.1016/j.mib.2018.07.002},
pmid = {30059804},
issn = {1879-0364},
support = {R01 HG004872/HG/NHGRI NIH HHS/United States ; R01 HL140976/HL/NHLBI NIH HHS/United States ; R01 MD011389/MD/NIMHD NIH HHS/United States ; },
abstract = {Hypothesis-driven research has led to many scientific advances, but hypotheses cannot be tested in isolation: rather, they require a framework of aggregated scientific knowledge to allow questions to be posed meaningfully. This framework is largely still lacking in microbiome studies, and the only way to create it is by discovery-driven, tool-driven, and standards-driven research projects. Here we illustrate these issues using several such non-hypothesis-driven projects from our own laboratories, including spatial mapping, the American Gut Project, the Earth Microbiome Project (which is an umbrella project integrating many smaller hypothesis-driven projects), and the knowledgebase-driven tools GNPS and Qiita. We argue that an investment of community resources in infrastructure tasks, and in the controls and standards that underpin them, will greatly enhance the investment in hypothesis-driven research programs.},
}

Atlantic cod (Gadus morhua) provides an interesting species for the study of host-microbe interactions because it lacks the MHC II complex that is involved in the presentation of extracellular pathogens. Nonetheless, little is known about the diversity of its microbiome in natural populations. Here, we use high-throughput sequencing of the 16S rRNA V4 region, amplified with the primer design of the Earth Microbiome Project (EMP), to investigate the microbial composition in gut content and mucosa of 22 adult individuals from two coastal populations in Norway, located 470 km apart. We identify a core microbiome of 23 OTUs (97% sequence similarity) in all individuals that comprises 93% of the total number of reads. The most abundant orders are classified as Vibrionales, Fusobacteriales, Clostridiales, and Bacteroidales. While mucosal samples show significantly lower diversity than gut content samples, no differences in OTU community composition are observed between the two geographically separated populations. All specimens share a limited number of abundant OTUs. Moreover, the most abundant OTU consists of a single oligotype (order Vibrionales, genus Photobacterium) that represents nearly 50% of the reads in both locations. Our results suggest that these microbiomes comprise a limited number of species or that the EMP V4 primers do not yield sufficient resolution to confidently separate these communities. Our study contributes to a growing body of literature that shows limited spatial differentiation of the intestinal microbiomes in marine fish based on 16S rRNA sequencing, highlighting the need for multi-gene approaches to provide more insight into the diversity of these communities.

@article {pmid30057577,
year = {2018},
author = {Riiser, ES and Haverkamp, THA and Borgan, Ø and Jakobsen, KS and Jentoft, S and Star, B},
title = {A Single Vibrionales 16S rRNA Oligotype Dominates the Intestinal Microbiome in Two Geographically Separated Atlantic cod Populations.},
journal = {Frontiers in microbiology},
volume = {9},
number = {},
pages = {1561},
doi = {10.3389/fmicb.2018.01561},
pmid = {30057577},
issn = {1664-302X},
abstract = {Atlantic cod (Gadus morhua) provides an interesting species for the study of host-microbe interactions because it lacks the MHC II complex that is involved in the presentation of extracellular pathogens. Nonetheless, little is known about the diversity of its microbiome in natural populations. Here, we use high-throughput sequencing of the 16S rRNA V4 region, amplified with the primer design of the Earth Microbiome Project (EMP), to investigate the microbial composition in gut content and mucosa of 22 adult individuals from two coastal populations in Norway, located 470 km apart. We identify a core microbiome of 23 OTUs (97% sequence similarity) in all individuals that comprises 93% of the total number of reads. The most abundant orders are classified as Vibrionales, Fusobacteriales, Clostridiales, and Bacteroidales. While mucosal samples show significantly lower diversity than gut content samples, no differences in OTU community composition are observed between the two geographically separated populations. All specimens share a limited number of abundant OTUs. Moreover, the most abundant OTU consists of a single oligotype (order Vibrionales, genus Photobacterium) that represents nearly 50% of the reads in both locations. Our results suggest that these microbiomes comprise a limited number of species or that the EMP V4 primers do not yield sufficient resolution to confidently separate these communities. Our study contributes to a growing body of literature that shows limited spatial differentiation of the intestinal microbiomes in marine fish based on 16S rRNA sequencing, highlighting the need for multi-gene approaches to provide more insight into the diversity of these communities.},
}

RevDate: 2018-11-14

Clayton JB, Al-Ghalith GA, Long HT, et al (2018)

Associations Between Nutrition, Gut Microbiome, and Health in A Novel Nonhuman Primate Model.

Scientific reports, 8(1):11159 pii:10.1038/s41598-018-29277-x.

Red-shanked doucs (Pygathrix nemaeus) are endangered, foregut-fermenting colobine primates which are difficult to maintain in captivity. There are critical gaps in our understanding of their natural lifestyle, including dietary habits such as consumption of leaves, unripe fruit, flowers, seeds, and other plant parts. There is also a lack of understanding of enteric adaptations, including their unique microflora. To address these knowledge gaps, we used the douc as a model to study relationships between gastrointestinal microbial community structure and lifestyle. We analyzed published fecal samples as well as detailed dietary history from doucs with four distinct lifestyles (wild, semi-wild, semi-captive, and captive) and determined gastrointestinal bacterial microbiome composition using 16S rRNA sequencing. A clear gradient of microbiome composition was revealed along an axis of natural lifestyle disruption, including significant associations with diet, biodiversity, and microbial function. We also identified potential microbial biomarkers of douc dysbiosis, including Bacteroides and Prevotella, which may be related to health. Our results suggest a gradient-like shift in captivity causes an attendant shift to severe gut dysbiosis, thereby resulting in gastrointestinal issues.

@article {pmid30042392,
year = {2018},
author = {Clayton, JB and Al-Ghalith, GA and Long, HT and Tuan, BV and Cabana, F and Huang, H and Vangay, P and Ward, T and Minh, VV and Tam, NA and Dat, NT and Travis, DA and Murtaugh, MP and Covert, H and Glander, KE and Nadler, T and Toddes, B and Sha, JCM and Singer, R and Knights, D and Johnson, TJ},
title = {Associations Between Nutrition, Gut Microbiome, and Health in A Novel Nonhuman Primate Model.},
journal = {Scientific reports},
volume = {8},
number = {1},
pages = {11159},
doi = {10.1038/s41598-018-29277-x},
pmid = {30042392},
issn = {2045-2322},
support = {T32 DA007097/DA/NIDA NIH HHS/United States ; },
abstract = {Red-shanked doucs (Pygathrix nemaeus) are endangered, foregut-fermenting colobine primates which are difficult to maintain in captivity. There are critical gaps in our understanding of their natural lifestyle, including dietary habits such as consumption of leaves, unripe fruit, flowers, seeds, and other plant parts. There is also a lack of understanding of enteric adaptations, including their unique microflora. To address these knowledge gaps, we used the douc as a model to study relationships between gastrointestinal microbial community structure and lifestyle. We analyzed published fecal samples as well as detailed dietary history from doucs with four distinct lifestyles (wild, semi-wild, semi-captive, and captive) and determined gastrointestinal bacterial microbiome composition using 16S rRNA sequencing. A clear gradient of microbiome composition was revealed along an axis of natural lifestyle disruption, including significant associations with diet, biodiversity, and microbial function. We also identified potential microbial biomarkers of douc dysbiosis, including Bacteroides and Prevotella, which may be related to health. Our results suggest a gradient-like shift in captivity causes an attendant shift to severe gut dysbiosis, thereby resulting in gastrointestinal issues.},
}

Motivation: The rapid development of sequencing technology has led to an explosive accumulation of genomic data. Clustering is often the ﬁrst step to be performed in sequence analysis. However, existing methods scale poorly with respect to the unprecedented growth of input data size. As high-performance computing systems are becoming widely accessible, it is highly desired that a clustering method can easily scale to handle large-scale sequence datasets by leveraging the power of parallel computing.

Results: In this paper, we introduce SLAD (Separation via Landmark-based Active Divisive clustering), a generic computational framework that can be used to parallelize various de novo operational taxonomic unit (OTU) picking methods and comes with theoretical guarantees on both accuracy and efﬁciency. The proposed framework was implemented on Apache Spark, which allows for easy and efﬁcient utilization of parallel computing resources. Experiments performed on various datasets demonstrated that SLAD can signiﬁcantly speed up a number of popular de novo OTU picking methods and meanwhile maintains the same level of accuracy. In particular, the experiment on the Earth Microbiome Project dataset (∼2.2B reads, 437GB) demonstrated the excellent scalability of the proposed method.

Open-source software for the proposed method is freely available at https://www.acsu.buffalo.edu/˜yijunsun/lab/SLAD.html.

Supplementary information: Supplementary data is available at Bioinformatics online.

@article {pmid30010718,
year = {2018},
author = {Zheng, W and Mao, Q and Genco, RJ and Wactawski-Wende, J and Buck, M and Cai, Y and Sun, Y},
title = {A parallel computational framework for ultra-large-scale sequence clustering analysis.},
journal = {Bioinformatics (Oxford, England)},
volume = {},
number = {},
pages = {},
doi = {10.1093/bioinformatics/bty617},
pmid = {30010718},
issn = {1367-4811},
abstract = {Motivation: The rapid development of sequencing technology has led to an explosive accumulation of genomic data. Clustering is often the ﬁrst step to be performed in sequence analysis. However, existing methods scale poorly with respect to the unprecedented growth of input data size. As high-performance computing systems are becoming widely accessible, it is highly desired that a clustering method can easily scale to handle large-scale sequence datasets by leveraging the power of parallel computing.

Results: In this paper, we introduce SLAD (Separation via Landmark-based Active Divisive clustering), a generic computational framework that can be used to parallelize various de novo operational taxonomic unit (OTU) picking methods and comes with theoretical guarantees on both accuracy and efﬁciency. The proposed framework was implemented on Apache Spark, which allows for easy and efﬁcient utilization of parallel computing resources. Experiments performed on various datasets demonstrated that SLAD can signiﬁcantly speed up a number of popular de novo OTU picking methods and meanwhile maintains the same level of accuracy. In particular, the experiment on the Earth Microbiome Project dataset (∼2.2B reads, 437GB) demonstrated the excellent scalability of the proposed method.

Open-source software for the proposed method is freely available at https://www.acsu.buffalo.edu/˜yijunsun/lab/SLAD.html.

Supplementary information: Supplementary data is available at Bioinformatics online.},
}

Benefit deriving from the use of light is known since ancient time, but, only in the last decades of twentieth century, we witnessed the rapid expansion of knowledge and techniques. Light-emitted diode (LED)-based devices represent the emerging and safest tool for the treatment of many conditions such as skin inflammatory conditions, aging, and disorders linked to hair growth. The present work reviews the current knowledge about LED-based therapeutic approaches in different skin and hair disorders. LED therapy represents the emerging and safest tool for the treatment of many conditions such as skin inflammatory conditions, aging, and disorders linked to hair growth. The use of LED in the treatment of such conditions has now entered common practice among dermatologists. Additional controlled studies are still needed to corroborate the efficacy of such kind of treatment.

@article {pmid30006754,
year = {2018},
author = {Sorbellini, E and Rucco, M and Rinaldi, F},
title = {Photodynamic and photobiological effects of light-emitting diode (LED) therapy in dermatological disease: an update.},
journal = {Lasers in medical science},
volume = {},
number = {},
pages = {},
doi = {10.1007/s10103-018-2584-8},
pmid = {30006754},
issn = {1435-604X},
abstract = {Benefit deriving from the use of light is known since ancient time, but, only in the last decades of twentieth century, we witnessed the rapid expansion of knowledge and techniques. Light-emitted diode (LED)-based devices represent the emerging and safest tool for the treatment of many conditions such as skin inflammatory conditions, aging, and disorders linked to hair growth. The present work reviews the current knowledge about LED-based therapeutic approaches in different skin and hair disorders. LED therapy represents the emerging and safest tool for the treatment of many conditions such as skin inflammatory conditions, aging, and disorders linked to hair growth. The use of LED in the treatment of such conditions has now entered common practice among dermatologists. Additional controlled studies are still needed to corroborate the efficacy of such kind of treatment.},
}

RevDate: 2018-07-09

Li BL, Cheng L, Zhou XD, et al (2018)

[Research progress on the relationship between oral microbes and digestive system diseases].

The human microbiome project promoted further understanding on human oral microbes. Besides oral diseases such as dental caries, periodontal disease, and oral cancer, oral microbes are closely associated with systematic diseases. They have a close connection with digestive system diseases and even contribute to the origination and progression of colorectal cancer. By reviewing recent studies involving oral microbe-related digestive systemic diseases, we aim to propose the considerable role of oral microbes in relation to digestive systemic diseases and the way of oral microbes to multiple organs of digestive system.

Patents as Early Indicators of Technology and Investment Trends: Analyzing the Microbiome Space as a Case Study.

Frontiers in bioengineering and biotechnology, 6:84.

The human microbiome is the collective of microbes living in symbiosis on and within humans. Modulating its composition and function has become an attractive means for the prevention and treatment of a variety of diseases including cancer. Since the initiation of the human microbiome project in 2007, the number of academic publications and active patent families around the microbiome has grown exponentially. Screening patent databases can be useful for the early detection and the tracking of new technology trends. However, it is not sufficient to assess portfolio sizes because emerging players with small but high-quality patent portfolios will be missed within the noise of large but low-quality portfolio owners. Here we used the consolidated database and software tool PatentSight to benchmark patent portfolios, and to analyze key patent owners and innovators in the microbiome space. Our study shows how in-depth patent analyses combining qualitative and quantitative parameters can identify actionable early indicators of technology and investment trends from large patent datasets.

@article {pmid29974051,
year = {2018},
author = {Fankhauser, M and Moser, C and Nyfeler, T},
title = {Patents as Early Indicators of Technology and Investment Trends: Analyzing the Microbiome Space as a Case Study.},
journal = {Frontiers in bioengineering and biotechnology},
volume = {6},
number = {},
pages = {84},
doi = {10.3389/fbioe.2018.00084},
pmid = {29974051},
issn = {2296-4185},
abstract = {The human microbiome is the collective of microbes living in symbiosis on and within humans. Modulating its composition and function has become an attractive means for the prevention and treatment of a variety of diseases including cancer. Since the initiation of the human microbiome project in 2007, the number of academic publications and active patent families around the microbiome has grown exponentially. Screening patent databases can be useful for the early detection and the tracking of new technology trends. However, it is not sufficient to assess portfolio sizes because emerging players with small but high-quality patent portfolios will be missed within the noise of large but low-quality portfolio owners. Here we used the consolidated database and software tool PatentSight to benchmark patent portfolios, and to analyze key patent owners and innovators in the microbiome space. Our study shows how in-depth patent analyses combining qualitative and quantitative parameters can identify actionable early indicators of technology and investment trends from large patent datasets.},
}

RevDate: 2018-10-10

Coleman M, Elkins C, Gutting B, et al (2018)

Microbiota and Dose Response: Evolving Paradigm of Health Triangle.

Risk analysis : an official publication of the Society for Risk Analysis, 38(10):2013-2028.

SRA Dose-Response and Microbial Risk Analysis Specialty Groups jointly sponsored symposia that addressed the intersections between the "microbiome revolution" and dose response. Invited speakers presented on innovations and advances in gut and nasal microbiota (normal microbial communities) in the first decade after the Human Microbiome Project began. The microbiota and their metabolites are now known to influence health and disease directly and indirectly, through modulation of innate and adaptive immune systems and barrier function. Disruption of healthy microbiota is often associated with changes in abundance and diversity of core microbial species (dysbiosis), caused by stressors including antibiotics, chemotherapy, and disease. Nucleic-acid-based metagenomic methods demonstrated that the dysbiotic host microbiota no longer provide normal colonization resistance to pathogens, a critical component of innate immunity of the superorganism. Diverse pathogens, probiotics, and prebiotics were considered in human and animal models (in vivo and in vitro). Discussion included approaches for design of future microbial dose-response studies to account for the presence of the indigenous microbiota that provide normal colonization resistance, and the absence of the protective microbiota in dysbiosis. As NextGen risk analysis methodology advances with the "microbiome revolution," a proposed new framework, the Health Triangle, may replace the old paradigm based on the Disease Triangle (focused on host, pathogen, and environment) and germophobia. Collaborative experimental designs are needed for testing hypotheses about causality in dose-response relationships for pathogens present in our environments that clearly compete in complex ecosystems with thousands of bacterial species dominating the healthy superorganism.

@article {pmid29900563,
year = {2018},
author = {Coleman, M and Elkins, C and Gutting, B and Mongodin, E and Solano-Aguilar, G and Walls, I},
title = {Microbiota and Dose Response: Evolving Paradigm of Health Triangle.},
journal = {Risk analysis : an official publication of the Society for Risk Analysis},
volume = {38},
number = {10},
pages = {2013-2028},
doi = {10.1111/risa.13121},
pmid = {29900563},
issn = {1539-6924},
abstract = {SRA Dose-Response and Microbial Risk Analysis Specialty Groups jointly sponsored symposia that addressed the intersections between the "microbiome revolution" and dose response. Invited speakers presented on innovations and advances in gut and nasal microbiota (normal microbial communities) in the first decade after the Human Microbiome Project began. The microbiota and their metabolites are now known to influence health and disease directly and indirectly, through modulation of innate and adaptive immune systems and barrier function. Disruption of healthy microbiota is often associated with changes in abundance and diversity of core microbial species (dysbiosis), caused by stressors including antibiotics, chemotherapy, and disease. Nucleic-acid-based metagenomic methods demonstrated that the dysbiotic host microbiota no longer provide normal colonization resistance to pathogens, a critical component of innate immunity of the superorganism. Diverse pathogens, probiotics, and prebiotics were considered in human and animal models (in vivo and in vitro). Discussion included approaches for design of future microbial dose-response studies to account for the presence of the indigenous microbiota that provide normal colonization resistance, and the absence of the protective microbiota in dysbiosis. As NextGen risk analysis methodology advances with the "microbiome revolution," a proposed new framework, the Health Triangle, may replace the old paradigm based on the Disease Triangle (focused on host, pathogen, and environment) and germophobia. Collaborative experimental designs are needed for testing hypotheses about causality in dose-response relationships for pathogens present in our environments that clearly compete in complex ecosystems with thousands of bacterial species dominating the healthy superorganism.},
}

Motivation: Identification of complex relationships among members of microbial communities is key to understand and control the microbiota. Co-exclusion is arguably one of the most important patterns reflecting micro-organisms' intolerance to each other's presence. Knowing these relations opens an opportunity to manipulate microbiotas, personalize anti-microbial and probiotic treatments as well as guide microbiota transplantation. The co-exclusion pattern however, cannot be appropriately described by a linear function nor its strength be estimated using covariance or (negative) Pearson and Spearman correlation coefficients. This manuscript proposes a way to quantify the strength and evaluate the statistical significance of co-exclusion patterns between two, three or more variables describing a microbiota and allows one to extend analysis beyond micro-organism abundance by including other microbiome associated measurements such as, pH, temperature etc., as well as estimate the expected numbers of false positive co-exclusion patterns in a co-exclusion network.

C++ source code for calculation of the score and P-value for two, three and four dimensional co-exclusion patterns as well as source code and executable files for the CoEx pipeline are available at https://scsb.utmb.edu/labgroups/fofanov/co-exclusion_in_microbial_communities.asp.

Supplementary information: Supplementary data are available at Bioinformatics online.

@article {pmid29878050,
year = {2018},
author = {Albayrak, L and Khanipov, K and Golovko, G and Fofanov, Y},
title = {Detection of multi-dimensional co-exclusion patterns in microbial communities.},
journal = {Bioinformatics (Oxford, England)},
volume = {34},
number = {21},
pages = {3695-3701},
doi = {10.1093/bioinformatics/bty414},
pmid = {29878050},
issn = {1367-4811},
abstract = {Motivation: Identification of complex relationships among members of microbial communities is key to understand and control the microbiota. Co-exclusion is arguably one of the most important patterns reflecting micro-organisms' intolerance to each other's presence. Knowing these relations opens an opportunity to manipulate microbiotas, personalize anti-microbial and probiotic treatments as well as guide microbiota transplantation. The co-exclusion pattern however, cannot be appropriately described by a linear function nor its strength be estimated using covariance or (negative) Pearson and Spearman correlation coefficients. This manuscript proposes a way to quantify the strength and evaluate the statistical significance of co-exclusion patterns between two, three or more variables describing a microbiota and allows one to extend analysis beyond micro-organism abundance by including other microbiome associated measurements such as, pH, temperature etc., as well as estimate the expected numbers of false positive co-exclusion patterns in a co-exclusion network.

C++ source code for calculation of the score and P-value for two, three and four dimensional co-exclusion patterns as well as source code and executable files for the CoEx pipeline are available at https://scsb.utmb.edu/labgroups/fofanov/co-exclusion_in_microbial_communities.asp.

Supplementary information: Supplementary data are available at Bioinformatics online.},
}

RevDate: 2018-06-22

Clayton JB, Gomez A, Amato K, et al (2018)

The gut microbiome of nonhuman primates: Lessons in ecology and evolution.

American journal of primatology, 80(6):e22867.

The mammalian gastrointestinal (GI) tract is home to trillions of bacteria that play a substantial role in host metabolism and immunity. While progress has been made in understanding the role that microbial communities play in human health and disease, much less attention has been given to host-associated microbiomes in nonhuman primates (NHPs). Here we review past and current research exploring the gut microbiome of NHPs. First, we summarize methods for characterization of the NHP gut microbiome. Then we discuss variation in gut microbiome composition and function across different NHP taxa. Finally, we highlight how studying the gut microbiome offers new insights into primate nutrition, physiology, and immune system function, as well as enhances our understanding of primate ecology and evolution. Microbiome approaches are useful tools for studying relevant issues in primate ecology. Further study of the gut microbiome of NHPs will offer new insight into primate ecology and evolution as well as human health.

@article {pmid29862519,
year = {2018},
author = {Clayton, JB and Gomez, A and Amato, K and Knights, D and Travis, DA and Blekhman, R and Knight, R and Leigh, S and Stumpf, R and Wolf, T and Glander, KE and Cabana, F and Johnson, TJ},
title = {The gut microbiome of nonhuman primates: Lessons in ecology and evolution.},
journal = {American journal of primatology},
volume = {80},
number = {6},
pages = {e22867},
doi = {10.1002/ajp.22867},
pmid = {29862519},
issn = {1098-2345},
abstract = {The mammalian gastrointestinal (GI) tract is home to trillions of bacteria that play a substantial role in host metabolism and immunity. While progress has been made in understanding the role that microbial communities play in human health and disease, much less attention has been given to host-associated microbiomes in nonhuman primates (NHPs). Here we review past and current research exploring the gut microbiome of NHPs. First, we summarize methods for characterization of the NHP gut microbiome. Then we discuss variation in gut microbiome composition and function across different NHP taxa. Finally, we highlight how studying the gut microbiome offers new insights into primate nutrition, physiology, and immune system function, as well as enhances our understanding of primate ecology and evolution. Microbiome approaches are useful tools for studying relevant issues in primate ecology. Further study of the gut microbiome of NHPs will offer new insight into primate ecology and evolution as well as human health.},
}

Host-associated microbial dynamics are influenced by dietary and immune factors, but how exogenous microbial exposure shapes host-microbe dynamics remains poorly characterized. To investigate this phenomenon, we characterized the skin, rectum, and respiratory tract-associated microbiota in four aquarium-housed dolphins daily over a period of 6 weeks, including administration of a probiotic during weeks 4 to 6. The environmental bacterial sources were also characterized, including the animals' human handlers, the aquarium air and water, and the dolphins' food supply. Continuous microbial exposure occurred between all sites, yet each environment maintained a characteristic microbiota, suggesting that the majority of exposure events do not result in colonization. Small changes in water physicochemistry had a significant but weak correlation with change in dolphin-associated bacterial richness but had no influence on phylogenetic diversity. Food and air microbiota were the richest and had the largest conditional influence on other microbiota in the absence of probiotics, but during probiotic administration, food alone had the largest influence on the stability of the dolphin microbiota. Our results suggest that respiratory tract and gastrointestinal epithelium interactions with air- and food-associated microbes had the biggest influence on host-microbiota dynamics, while other interactions, such as skin transmission, played only a minor role. Finally, direct oral stimulation with a foreign exogenous microbial source can have a profound effect on microbial stability. IMPORTANCE These results provide valuable insights into the ecological influence of exogenous microbial exposure, as well as laying the foundation for improving aquarium management practices. By comparing data for dolphins from aquaria that use natural versus artificial seawater, we demonstrate the potential influence of aquarium water disinfection procedures on dolphin microbial dynamics.

@article {pmid29854953,
year = {2018},
author = {Cardona, C and Lax, S and Larsen, P and Stephens, B and Hampton-Marcell, J and Edwardson, CF and Henry, C and Van Bonn, B and Gilbert, JA},
title = {Environmental Sources of Bacteria Differentially Influence Host-Associated Microbial Dynamics.},
journal = {mSystems},
volume = {3},
number = {3},
pages = {},
doi = {10.1128/mSystems.00052-18},
pmid = {29854953},
issn = {2379-5077},
support = {P30 DK042086/DK/NIDDK NIH HHS/United States ; },
abstract = {Host-associated microbial dynamics are influenced by dietary and immune factors, but how exogenous microbial exposure shapes host-microbe dynamics remains poorly characterized. To investigate this phenomenon, we characterized the skin, rectum, and respiratory tract-associated microbiota in four aquarium-housed dolphins daily over a period of 6 weeks, including administration of a probiotic during weeks 4 to 6. The environmental bacterial sources were also characterized, including the animals' human handlers, the aquarium air and water, and the dolphins' food supply. Continuous microbial exposure occurred between all sites, yet each environment maintained a characteristic microbiota, suggesting that the majority of exposure events do not result in colonization. Small changes in water physicochemistry had a significant but weak correlation with change in dolphin-associated bacterial richness but had no influence on phylogenetic diversity. Food and air microbiota were the richest and had the largest conditional influence on other microbiota in the absence of probiotics, but during probiotic administration, food alone had the largest influence on the stability of the dolphin microbiota. Our results suggest that respiratory tract and gastrointestinal epithelium interactions with air- and food-associated microbes had the biggest influence on host-microbiota dynamics, while other interactions, such as skin transmission, played only a minor role. Finally, direct oral stimulation with a foreign exogenous microbial source can have a profound effect on microbial stability. IMPORTANCE These results provide valuable insights into the ecological influence of exogenous microbial exposure, as well as laying the foundation for improving aquarium management practices. By comparing data for dolphins from aquaria that use natural versus artificial seawater, we demonstrate the potential influence of aquarium water disinfection procedures on dolphin microbial dynamics.},
}

RevDate: 2018-11-14

McDonald D, Hyde E, Debelius JW, et al (2018)

American Gut: an Open Platform for Citizen Science Microbiome Research.

mSystems, 3(3): pii:mSystems00031-18.

Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. IMPORTANCE We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples.

@article {pmid29795809,
year = {2018},
author = {McDonald, D and Hyde, E and Debelius, JW and Morton, JT and Gonzalez, A and Ackermann, G and Aksenov, AA and Behsaz, B and Brennan, C and Chen, Y and DeRight Goldasich, L and Dorrestein, PC and Dunn, RR and Fahimipour, AK and Gaffney, J and Gilbert, JA and Gogul, G and Green, JL and Hugenholtz, P and Humphrey, G and Huttenhower, C and Jackson, MA and Janssen, S and Jeste, DV and Jiang, L and Kelley, ST and Knights, D and Kosciolek, T and Ladau, J and Leach, J and Marotz, C and Meleshko, D and Melnik, AV and Metcalf, JL and Mohimani, H and Montassier, E and Navas-Molina, J and Nguyen, TT and Peddada, S and Pevzner, P and Pollard, KS and Rahnavard, G and Robbins-Pianka, A and Sangwan, N and Shorenstein, J and Smarr, L and Song, SJ and Spector, T and Swafford, AD and Thackray, VG and Thompson, LR and Tripathi, A and Vázquez-Baeza, Y and Vrbanac, A and Wischmeyer, P and Wolfe, E and Zhu, Q and , and Knight, R},
title = {American Gut: an Open Platform for Citizen Science Microbiome Research.},
journal = {mSystems},
volume = {3},
number = {3},
pages = {},
doi = {10.1128/mSystems.00031-18},
pmid = {29795809},
issn = {2379-5077},
support = {//Wellcome Trust/United Kingdom ; P30 DK042086/DK/NIDDK NIH HHS/United States ; P30 DK043351/DK/NIDDK NIH HHS/United States ; },
abstract = {Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. IMPORTANCE We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples.},
}

The human microbiome project (HMP) promoted further understanding of human oral microbes. However, research on the human oral microbiota has not made as much progress as research on the gut microbiota. Currently, the causal relationship between the oral microbiota and oral diseases remains unclear, and little is known about the link between the oral microbiota and human systemic diseases. To further understand the contribution of the oral microbiota in oral diseases and systemic diseases, a Human Oral Microbiome Database (HOMD) was established in the US. The HOMD includes 619 taxa in 13 phyla, and most of the microorganisms are from American populations. Due to individual differences in the microbiome, the HOMD does not reflect the Chinese oral microbial status. Herein, we established a new oral microbiome database-the Oral Microbiome Bank of China (OMBC, http://www.sklod.org/ombc). Currently, the OMBC includes information on 289 bacterial strains and 720 clinical samples from the Chinese population, along with lab and clinical information. The OMBC is the first curated description of a Chinese-associated microbiome; it provides tools for use in investigating the role of the oral microbiome in health and diseases, and will give the community abundant data and strain information for future oral microbial studies.

@article {pmid29760467,
year = {2018},
author = {Xian, P and Xuedong, Z and Xin, X and Yuqing, L and Yan, L and Jiyao, L and Xiaoquan, S and Shi, H and Jian, X and Ga, L},
title = {The Oral Microbiome Bank of China.},
journal = {International journal of oral science},
volume = {10},
number = {2},
pages = {16},
doi = {10.1038/s41368-018-0018-x},
pmid = {29760467},
issn = {2049-3169},
abstract = {The human microbiome project (HMP) promoted further understanding of human oral microbes. However, research on the human oral microbiota has not made as much progress as research on the gut microbiota. Currently, the causal relationship between the oral microbiota and oral diseases remains unclear, and little is known about the link between the oral microbiota and human systemic diseases. To further understand the contribution of the oral microbiota in oral diseases and systemic diseases, a Human Oral Microbiome Database (HOMD) was established in the US. The HOMD includes 619 taxa in 13 phyla, and most of the microorganisms are from American populations. Due to individual differences in the microbiome, the HOMD does not reflect the Chinese oral microbial status. Herein, we established a new oral microbiome database-the Oral Microbiome Bank of China (OMBC, http://www.sklod.org/ombc). Currently, the OMBC includes information on 289 bacterial strains and 720 clinical samples from the Chinese population, along with lab and clinical information. The OMBC is the first curated description of a Chinese-associated microbiome; it provides tools for use in investigating the role of the oral microbiome in health and diseases, and will give the community abundant data and strain information for future oral microbial studies.},
}

The maternal microbiota plays an important role in infant gut colonization. In this work we have investigated which bacterial species are shared across the breast milk, vaginal and stool microbiotas of 109 women shortly before and after giving birth using 16S rRNA gene sequencing and a novel reduced metagenomic sequencing (RMS) approach in a subgroup of 16 women. All the species predicted by the 16S rRNA gene sequencing were also detected by RMS analysis and there was good correspondence between their relative abundances estimated by both approaches. Both approaches also demonstrate a low level of maternal microbiota sharing across the population and RMS analysis identified only two species common to most women and in all sample types (Bifidobacterium longum and Enterococcus faecalis). Breast milk was the only sample type that had significantly higher intra- than inter- individual similarity towards both vaginal and stool samples. We also searched our RMS dataset against an in silico generated reference database derived from bacterial isolates in the Human Microbiome Project. The use of this reference-based search enabled further separation of Bifidobacterium longum into Bifidobacterium longum ssp. longum and Bifidobacterium longum ssp. infantis. We also detected the Lactobacillus rhamnosus GG strain, which was used as a probiotic supplement by some women, demonstrating the potential of RMS approach for deeper taxonomic delineation and estimation.

@article {pmid29724017,
year = {2018},
author = {Avershina, E and Angell, IL and Simpson, M and Storrø, O and Øien, T and Johnsen, R and Rudi, K},
title = {Low Maternal Microbiota Sharing across Gut, Breast Milk and Vagina, as Revealed by 16S rRNA Gene and Reduced Metagenomic Sequencing.},
journal = {Genes},
volume = {9},
number = {5},
pages = {},
doi = {10.3390/genes9050231},
pmid = {29724017},
issn = {2073-4425},
abstract = {The maternal microbiota plays an important role in infant gut colonization. In this work we have investigated which bacterial species are shared across the breast milk, vaginal and stool microbiotas of 109 women shortly before and after giving birth using 16S rRNA gene sequencing and a novel reduced metagenomic sequencing (RMS) approach in a subgroup of 16 women. All the species predicted by the 16S rRNA gene sequencing were also detected by RMS analysis and there was good correspondence between their relative abundances estimated by both approaches. Both approaches also demonstrate a low level of maternal microbiota sharing across the population and RMS analysis identified only two species common to most women and in all sample types (Bifidobacterium longum and Enterococcus faecalis). Breast milk was the only sample type that had significantly higher intra- than inter- individual similarity towards both vaginal and stool samples. We also searched our RMS dataset against an in silico generated reference database derived from bacterial isolates in the Human Microbiome Project. The use of this reference-based search enabled further separation of Bifidobacterium longum into Bifidobacterium longum ssp. longum and Bifidobacterium longum ssp. infantis. We also detected the Lactobacillus rhamnosus GG strain, which was used as a probiotic supplement by some women, demonstrating the potential of RMS approach for deeper taxonomic delineation and estimation.},
}

RevDate: 2018-08-29

Rowan S, A Taylor (2018)

The Role of Microbiota in Retinal Disease.

Advances in experimental medicine and biology, 1074:429-435.

The ten years since the first publications on the human microbiome project have brought enormous attention and insight into the role of the human microbiome in health and disease. Connections between populations of microbiota and ocular disease are now being established, and increased accessibility to microbiome research and insights into other diseases is expected to yield enormous information in the coming years. With the characterization of the ocular microbiome, important insights have already been made regarding corneal and conjunctival tissues. Roles for non-ocular microbiomes in complex retinal diseases are now being evaluated. For example, the gut microbiome has been implicated in the pathogenesis of uveitis. This short review will summarize the few studies linking gut or oral microbiota to diabetic retinopathy (DR), glaucoma, and age-related macular degeneration (AMD). We will also conjecture where the most significant findings still remain to be elucidated. Finally, we will propose the gut-retina axis, related but distinct from the gut-brain axis.

@article {pmid29721973,
year = {2018},
author = {Rowan, S and Taylor, A},
title = {The Role of Microbiota in Retinal Disease.},
journal = {Advances in experimental medicine and biology},
volume = {1074},
number = {},
pages = {429-435},
doi = {10.1007/978-3-319-75402-4_53},
pmid = {29721973},
issn = {0065-2598},
abstract = {The ten years since the first publications on the human microbiome project have brought enormous attention and insight into the role of the human microbiome in health and disease. Connections between populations of microbiota and ocular disease are now being established, and increased accessibility to microbiome research and insights into other diseases is expected to yield enormous information in the coming years. With the characterization of the ocular microbiome, important insights have already been made regarding corneal and conjunctival tissues. Roles for non-ocular microbiomes in complex retinal diseases are now being evaluated. For example, the gut microbiome has been implicated in the pathogenesis of uveitis. This short review will summarize the few studies linking gut or oral microbiota to diabetic retinopathy (DR), glaucoma, and age-related macular degeneration (AMD). We will also conjecture where the most significant findings still remain to be elucidated. Finally, we will propose the gut-retina axis, related but distinct from the gut-brain axis.},
}

RevDate: 2018-11-14

Roche-Lima A, Carrasquillo-Carrión K, Gómez-Moreno R, et al (2018)

The Presence of Genotoxic and/or Pro-inflammatory Bacterial Genes in Gut Metagenomic Databases and Their Possible Link With Inflammatory Bowel Diseases.

Frontiers in genetics, 9:116.

Background: The human gut microbiota is a dynamic community of microorganisms that mediate important biochemical processes. Differences in the gut microbial composition have been associated with inflammatory bowel diseases (IBD) and other intestinal disorders. In this study, we quantified and compared the frequencies of eight genotoxic and/or pro-inflammatory bacterial genes found in metagenomic Whole Genome Sequences (mWGSs) of samples from individuals with IBD vs. a cohort of healthy human subjects. Methods: The eight selected gene sequences were clbN, clbB, cif, cnf-1, usp, tcpC from Escherichia coli, gelE from Enterococcus faecalis and murB from Akkermansia muciniphila. We also included the sequences for the conserved murB genes from E. coli and E. faecalis as markers for the presence of Enterobacteriaceae or Enterococci in the samples. The gene sequences were chosen based on their previously reported ability to disrupt normal cellular processes to either promote inflammation or to cause DNA damage in cultured cells or animal models, which could be linked to a role in IBD. The selected sequences were searched in three different mWGS datasets accessed through the Human Microbiome Project (HMP): a healthy cohort (N = 251), a Crohn's disease cohort (N = 60) and an ulcerative colitis cohort (N = 17). Results: Firstly, the sequences for the murB housekeeping genes from Enterobacteriaceae and Enterococci were more frequently found in the IBD cohorts (32% E. coli in IBD vs. 12% in healthy; 13% E. faecalis in IBD vs. 3% in healthy) than in the healthy cohort, confirming earlier reports of a higher presence of both of these taxa in IBD. For some of the sequences in our study, especially usp and gelE, their frequency was even more sharply increased in the IBD cohorts than in the healthy cohort, suggesting an association with IBD that is not easily explained by the increased presence of E. coli or E. faecalis in those samples. Conclusion: Our results suggest a significant association between the presence of some of these genotoxic or pro-inflammatory gene sequences and IBDs. In addition, these results illustrate the power and limitations of the HMP database in the detection of possible clinical correlations for individual bacterial genes.

@article {pmid29692798,
year = {2018},
author = {Roche-Lima, A and Carrasquillo-Carrión, K and Gómez-Moreno, R and Cruz, JM and Velázquez-Morales, DM and Rogozin, IB and Baerga-Ortiz, A},
title = {The Presence of Genotoxic and/or Pro-inflammatory Bacterial Genes in Gut Metagenomic Databases and Their Possible Link With Inflammatory Bowel Diseases.},
journal = {Frontiers in genetics},
volume = {9},
number = {},
pages = {116},
doi = {10.3389/fgene.2018.00116},
pmid = {29692798},
issn = {1664-8021},
support = {U54 MD007600/MD/NIMHD NIH HHS/United States ; R25 GM061838/GM/NIGMS NIH HHS/United States ; G12 RR003051/RR/NCRR NIH HHS/United States ; G12 MD007600/MD/NIMHD NIH HHS/United States ; R21 CA198963/CA/NCI NIH HHS/United States ; },
abstract = {Background: The human gut microbiota is a dynamic community of microorganisms that mediate important biochemical processes. Differences in the gut microbial composition have been associated with inflammatory bowel diseases (IBD) and other intestinal disorders. In this study, we quantified and compared the frequencies of eight genotoxic and/or pro-inflammatory bacterial genes found in metagenomic Whole Genome Sequences (mWGSs) of samples from individuals with IBD vs. a cohort of healthy human subjects. Methods: The eight selected gene sequences were clbN, clbB, cif, cnf-1, usp, tcpC from Escherichia coli, gelE from Enterococcus faecalis and murB from Akkermansia muciniphila. We also included the sequences for the conserved murB genes from E. coli and E. faecalis as markers for the presence of Enterobacteriaceae or Enterococci in the samples. The gene sequences were chosen based on their previously reported ability to disrupt normal cellular processes to either promote inflammation or to cause DNA damage in cultured cells or animal models, which could be linked to a role in IBD. The selected sequences were searched in three different mWGS datasets accessed through the Human Microbiome Project (HMP): a healthy cohort (N = 251), a Crohn's disease cohort (N = 60) and an ulcerative colitis cohort (N = 17). Results: Firstly, the sequences for the murB housekeeping genes from Enterobacteriaceae and Enterococci were more frequently found in the IBD cohorts (32% E. coli in IBD vs. 12% in healthy; 13% E. faecalis in IBD vs. 3% in healthy) than in the healthy cohort, confirming earlier reports of a higher presence of both of these taxa in IBD. For some of the sequences in our study, especially usp and gelE, their frequency was even more sharply increased in the IBD cohorts than in the healthy cohort, suggesting an association with IBD that is not easily explained by the increased presence of E. coli or E. faecalis in those samples. Conclusion: Our results suggest a significant association between the presence of some of these genotoxic or pro-inflammatory gene sequences and IBDs. In addition, these results illustrate the power and limitations of the HMP database in the detection of possible clinical correlations for individual bacterial genes.},
}

Motivation: Comparisons of microbiome communities across populations are often based on pairwise distance measures (beta-diversity). Standard analyses (principal coordinate plots, permutation tests, kernel methods) require access to primary data if another investigator wants to add or compare independent data. We propose using standard reference measurements to simplify microbiome beta-diversity analyses, to make them more transparent, and to facilitate independent validation and comparisons across studies.

Results: Using stool and nasal reference sets from the Human Microbiome Project (HMP), we computed mean distances (actually Bray-Curtis or Pearson correlation dissimilarities) to each reference set for each new sample. Thus, each new sample has two mean distances that can be plotted and analyzed with classical statistical methods. To test the approach, we studied independent (not reference) HMP subjects. Simple Hotelling tests demonstrated statistically significant differences in mean distances to reference sets between all pairs of body sites (stool, skin, nasal, saliva and vagina) at the phylum, class, order, family and genus levels. Using the distance to a single reference set was usually sufficient, but using both reference sets always worked well. The use of reference sets simplifies standard analyses of beta-diversity and facilitates the independent validation and combining of such data because others can compute distances to the same reference sets. Moreover, standard statistical methods for survival analysis, logistic regression and other procedures can be applied to vectors of mean distances to reference sets, thereby greatly expanding the potential uses of beta-diversity information. More work is needed to identify the best reference sets for particular applications.

https://github.com/NCI-biostats/microbiome-fixed-reference.

Supplementary information: Supplementary data are available at Bioinformatics online.

Results: Using stool and nasal reference sets from the Human Microbiome Project (HMP), we computed mean distances (actually Bray-Curtis or Pearson correlation dissimilarities) to each reference set for each new sample. Thus, each new sample has two mean distances that can be plotted and analyzed with classical statistical methods. To test the approach, we studied independent (not reference) HMP subjects. Simple Hotelling tests demonstrated statistically significant differences in mean distances to reference sets between all pairs of body sites (stool, skin, nasal, saliva and vagina) at the phylum, class, order, family and genus levels. Using the distance to a single reference set was usually sufficient, but using both reference sets always worked well. The use of reference sets simplifies standard analyses of beta-diversity and facilitates the independent validation and combining of such data because others can compute distances to the same reference sets. Moreover, standard statistical methods for survival analysis, logistic regression and other procedures can be applied to vectors of mean distances to reference sets, thereby greatly expanding the potential uses of beta-diversity information. More work is needed to identify the best reference sets for particular applications.

https://github.com/NCI-biostats/microbiome-fixed-reference.

Supplementary information: Supplementary data are available at Bioinformatics online.},
}

We introduce GATTACA, a framework for fast unsupervised binning of metagenomic contigs. Similar to recent approaches, GATTACA clusters contigs based on their coverage profiles across a large cohort of metagenomic samples; however, unlike previous methods that rely on read mapping, GATTACA quickly estimates these profiles from kmer counts stored in a compact index. This approach can result in over an order of magnitude speedup, while matching the accuracy of earlier methods on synthetic and real data benchmarks. It also provides a way to index metagenomic samples (e.g., from public repositories such as the Human Microbiome Project) offline once and reuse them across experiments; furthermore, the small size of the sample indices allows them to be easily transferred and stored. Leveraging the MinHash technique, GATTACA also provides an efficient way to identify publicly available metagenomic data that can be incorporated into the set of reference metagenomes to further improve binning accuracy. Thus, enabling easy indexing and reuse of publicly available metagenomic data sets, GATTACA makes accurate metagenomic analyses accessible to a much wider range of researchers.

@article {pmid29658784,
year = {2018},
author = {Popic, V and Kuleshov, V and Snyder, M and Batzoglou, S},
title = {Fast Metagenomic Binning via Hashing and Bayesian Clustering.},
journal = {Journal of computational biology : a journal of computational molecular cell biology},
volume = {25},
number = {7},
pages = {677-688},
doi = {10.1089/cmb.2017.0250},
pmid = {29658784},
issn = {1557-8666},
abstract = {We introduce GATTACA, a framework for fast unsupervised binning of metagenomic contigs. Similar to recent approaches, GATTACA clusters contigs based on their coverage profiles across a large cohort of metagenomic samples; however, unlike previous methods that rely on read mapping, GATTACA quickly estimates these profiles from kmer counts stored in a compact index. This approach can result in over an order of magnitude speedup, while matching the accuracy of earlier methods on synthetic and real data benchmarks. It also provides a way to index metagenomic samples (e.g., from public repositories such as the Human Microbiome Project) offline once and reuse them across experiments; furthermore, the small size of the sample indices allows them to be easily transferred and stored. Leveraging the MinHash technique, GATTACA also provides an efficient way to identify publicly available metagenomic data that can be incorporated into the set of reference metagenomes to further improve binning accuracy. Thus, enabling easy indexing and reuse of publicly available metagenomic data sets, GATTACA makes accurate metagenomic analyses accessible to a much wider range of researchers.},
}

Temporal variation in microbiome measurements can reduce statistical power in research studies. Quantification of this variation is essential for designing studies of chronic disease. We analyzed 16S ribosomal RNA profiles in paired biological specimens separated by 6 months from 3 studies conducted during 1985-2013 (a National Cancer Institute colorectal cancer study, a Costa Rica study, and the Human Microbiome Project). We evaluated temporal stability by calculating intraclass correlation coefficients (ICCs). Sample sizes needed in order to detect microbiome differences between equal numbers of cases and controls for a nested case-control design were calculated on the basis of estimated ICCs. Across body sites, 12 phylum-level ICCs were greater than 0.5. Similarly, 11 alpha-diversity ICCs were greater than 0.5. Fecal beta-diversity estimates had ICCs over 0.5. For a single collection with most microbiome metrics, detecting an odds ratio of 2.0 would require 300-500 cases when matching 1 case to 1 control at P = 0.05. Use of 2 or 3 sequential specimens reduces the number of required subjects by 40%-50% for low-ICC metrics. Relative abundances of major phyla and alpha-diversity metrics have low temporal stability. Thus, detecting associations of moderate effect size with these metrics will require large sample sizes. Because beta diversity for feces is reasonably stable over time, smaller sample sizes can detect associations with community composition. Sequential prediagnostic specimens from thousands of prospectively ascertained cases are required to detect modest disease associations with particular microbiome metrics.

@article {pmid29608646,
year = {2018},
author = {Sinha, R and Goedert, JJ and Vogtmann, E and Hua, X and Porras, C and Hayes, R and Safaeian, M and Yu, G and Sampson, J and Ahn, J and Shi, J},
title = {Quantification of Human Microbiome Stability Over 6 Months: Implications for Epidemiologic Studies.},
journal = {American journal of epidemiology},
volume = {187},
number = {6},
pages = {1282-1290},
doi = {10.1093/aje/kwy064},
pmid = {29608646},
issn = {1476-6256},
support = {R03 CA159414/CA/NCI NIH HHS/United States ; },
abstract = {Temporal variation in microbiome measurements can reduce statistical power in research studies. Quantification of this variation is essential for designing studies of chronic disease. We analyzed 16S ribosomal RNA profiles in paired biological specimens separated by 6 months from 3 studies conducted during 1985-2013 (a National Cancer Institute colorectal cancer study, a Costa Rica study, and the Human Microbiome Project). We evaluated temporal stability by calculating intraclass correlation coefficients (ICCs). Sample sizes needed in order to detect microbiome differences between equal numbers of cases and controls for a nested case-control design were calculated on the basis of estimated ICCs. Across body sites, 12 phylum-level ICCs were greater than 0.5. Similarly, 11 alpha-diversity ICCs were greater than 0.5. Fecal beta-diversity estimates had ICCs over 0.5. For a single collection with most microbiome metrics, detecting an odds ratio of 2.0 would require 300-500 cases when matching 1 case to 1 control at P = 0.05. Use of 2 or 3 sequential specimens reduces the number of required subjects by 40%-50% for low-ICC metrics. Relative abundances of major phyla and alpha-diversity metrics have low temporal stability. Thus, detecting associations of moderate effect size with these metrics will require large sample sizes. Because beta diversity for feces is reasonably stable over time, smaller sample sizes can detect associations with community composition. Sequential prediagnostic specimens from thousands of prospectively ascertained cases are required to detect modest disease associations with particular microbiome metrics.},
}

RevDate: 2018-11-14

Flores Saiffe Farías A, Mendizabal AP, JA Morales (2018)

An Ontology Systems Approach on Human Brain Expression and Metaproteomics.

Frontiers in microbiology, 9:406.

Research in the last decade has shown growing evidence of the gut microbiota influence on brain physiology. While many mechanisms of this influence have been proposed in animal models, most studies in humans are the result of a pathology-dysbiosis association and very few have related the presence of certain taxa with brain substructures or molecular pathways. In this paper, we associated the functional ontologies in the differential expression of brain substructures from the Allen Brain Atlas database, with those of the metaproteome from the Human Microbiome Project. Our results showed several coherent clustered ontologies where many taxa could influence brain expression and physiology. A detailed analysis of psychobiotics showed specific slim ontologies functionally associated with substructures in the basal ganglia and cerebellar cortex. Some of the most relevant slim ontology groups are related to Ion transport, Membrane potential, Synapse, DNA and RNA metabolism, and Antigen processing, while the most relevant neuropathology found was Parkinson disease. In some of these cases, new hypothetical gut microbiota-brain interaction pathways are proposed.

@article {pmid29568289,
year = {2018},
author = {Flores Saiffe Farías, A and Mendizabal, AP and Morales, JA},
title = {An Ontology Systems Approach on Human Brain Expression and Metaproteomics.},
journal = {Frontiers in microbiology},
volume = {9},
number = {},
pages = {406},
doi = {10.3389/fmicb.2018.00406},
pmid = {29568289},
issn = {1664-302X},
abstract = {Research in the last decade has shown growing evidence of the gut microbiota influence on brain physiology. While many mechanisms of this influence have been proposed in animal models, most studies in humans are the result of a pathology-dysbiosis association and very few have related the presence of certain taxa with brain substructures or molecular pathways. In this paper, we associated the functional ontologies in the differential expression of brain substructures from the Allen Brain Atlas database, with those of the metaproteome from the Human Microbiome Project. Our results showed several coherent clustered ontologies where many taxa could influence brain expression and physiology. A detailed analysis of psychobiotics showed specific slim ontologies functionally associated with substructures in the basal ganglia and cerebellar cortex. Some of the most relevant slim ontology groups are related to Ion transport, Membrane potential, Synapse, DNA and RNA metabolism, and Antigen processing, while the most relevant neuropathology found was Parkinson disease. In some of these cases, new hypothetical gut microbiota-brain interaction pathways are proposed.},
}

RevDate: 2018-11-14

Lang JM, Coil DA, Neches RY, et al (2017)

A microbial survey of the International Space Station (ISS).

PeerJ, 5:e4029 pii:4029.

Background: Modern advances in sequencing technology have enabled the census of microbial members of many natural ecosystems. Recently, attention is increasingly being paid to the microbial residents of human-made, built ecosystems, both private (homes) and public (subways, office buildings, and hospitals). Here, we report results of the characterization of the microbial ecology of a singular built environment, the International Space Station (ISS). This ISS sampling involved the collection and microbial analysis (via 16S rDNA PCR) of 15 surfaces sampled by swabs onboard the ISS. This sampling was a component of Project MERCCURI (Microbial Ecology Research Combining Citizen and University Researchers on ISS). Learning more about the microbial inhabitants of the "buildings" in which we travel through space will take on increasing importance, as plans for human exploration continue, with the possibility of colonization of other planets and moons.

Results: Sterile swabs were used to sample 15 surfaces onboard the ISS. The sites sampled were designed to be analogous to samples collected for (1) the Wildlife of Our Homes project and (2) a study of cell phones and shoes that were concurrently being collected for another component of Project MERCCURI. Sequencing of the 16S rDNA genes amplified from DNA extracted from each swab was used to produce a census of the microbes present on each surface sampled. We compared the microbes found on the ISS swabs to those from both homes on Earth and data from the Human Microbiome Project.

Conclusions: While significantly different from homes on Earth and the Human Microbiome Project samples analyzed here, the microbial community composition on the ISS was more similar to home surfaces than to the human microbiome samples. The ISS surfaces are species-rich with 1,036-4,294 operational taxonomic units (OTUs per sample). There was no discernible biogeography of microbes on the 15 ISS surfaces, although this may be a reflection of the small sample size we were able to obtain.

@article {pmid29492330,
year = {2017},
author = {Lang, JM and Coil, DA and Neches, RY and Brown, WE and Cavalier, D and Severance, M and Hampton-Marcell, JT and Gilbert, JA and Eisen, JA},
title = {A microbial survey of the International Space Station (ISS).},
journal = {PeerJ},
volume = {5},
number = {},
pages = {e4029},
doi = {10.7717/peerj.4029},
pmid = {29492330},
issn = {2167-8359},
support = {P30 DK042086/DK/NIDDK NIH HHS/United States ; },
abstract = {Background: Modern advances in sequencing technology have enabled the census of microbial members of many natural ecosystems. Recently, attention is increasingly being paid to the microbial residents of human-made, built ecosystems, both private (homes) and public (subways, office buildings, and hospitals). Here, we report results of the characterization of the microbial ecology of a singular built environment, the International Space Station (ISS). This ISS sampling involved the collection and microbial analysis (via 16S rDNA PCR) of 15 surfaces sampled by swabs onboard the ISS. This sampling was a component of Project MERCCURI (Microbial Ecology Research Combining Citizen and University Researchers on ISS). Learning more about the microbial inhabitants of the "buildings" in which we travel through space will take on increasing importance, as plans for human exploration continue, with the possibility of colonization of other planets and moons.

Results: Sterile swabs were used to sample 15 surfaces onboard the ISS. The sites sampled were designed to be analogous to samples collected for (1) the Wildlife of Our Homes project and (2) a study of cell phones and shoes that were concurrently being collected for another component of Project MERCCURI. Sequencing of the 16S rDNA genes amplified from DNA extracted from each swab was used to produce a census of the microbes present on each surface sampled. We compared the microbes found on the ISS swabs to those from both homes on Earth and data from the Human Microbiome Project.

Conclusions: While significantly different from homes on Earth and the Human Microbiome Project samples analyzed here, the microbial community composition on the ISS was more similar to home surfaces than to the human microbiome samples. The ISS surfaces are species-rich with 1,036-4,294 operational taxonomic units (OTUs per sample). There was no discernible biogeography of microbes on the 15 ISS surfaces, although this may be a reflection of the small sample size we were able to obtain.},
}

RevDate: 2018-03-01

Wu WK, Chen CC, Panyod S, et al (2018)

Optimization of fecal sample processing for microbiome study - The journey from bathroom to bench.

Although great interest has been displayed by researchers in the contribution of gut microbiota to human health, there is still no standard protocol with consensus to guarantee the sample quality of metagenomic analysis. Here we reviewed existing methodology studies and present suggestions for optimizing research pipeline from fecal sample collection to DNA extraction. First, we discuss strategies of clinical metadata collection as common confounders for microbiome research. Second, we propose general principles for freshly collected fecal sample and its storage and share a DIY stool collection kit protocol based on the manual procedure of Human Microbiome Project (HMP). Third, we provide a useful information of collection kit with DNA stabilization buffers and compare their pros and cons for multi-omic study. Fourth, we offer technical strategies as well as information of novel tools for sample aliquoting before long-term storage. Fifth, we discuss the substantial impact of different DNA extraction protocols on technical variations of metagenomic analysis. And lastly, we point out the limitation of current methods and the unmet needs for better quality control of metagenomic analysis. We hope the information provided here will help investigators in this exciting field to advance their studies while avoiding experimental artifacts.

@article {pmid29490879,
year = {2018},
author = {Wu, WK and Chen, CC and Panyod, S and Chen, RA and Wu, MS and Sheen, LY and Chang, SC},
title = {Optimization of fecal sample processing for microbiome study - The journey from bathroom to bench.},
journal = {Journal of the Formosan Medical Association = Taiwan yi zhi},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.jfma.2018.02.005},
pmid = {29490879},
issn = {0929-6646},
abstract = {Although great interest has been displayed by researchers in the contribution of gut microbiota to human health, there is still no standard protocol with consensus to guarantee the sample quality of metagenomic analysis. Here we reviewed existing methodology studies and present suggestions for optimizing research pipeline from fecal sample collection to DNA extraction. First, we discuss strategies of clinical metadata collection as common confounders for microbiome research. Second, we propose general principles for freshly collected fecal sample and its storage and share a DIY stool collection kit protocol based on the manual procedure of Human Microbiome Project (HMP). Third, we provide a useful information of collection kit with DNA stabilization buffers and compare their pros and cons for multi-omic study. Fourth, we offer technical strategies as well as information of novel tools for sample aliquoting before long-term storage. Fifth, we discuss the substantial impact of different DNA extraction protocols on technical variations of metagenomic analysis. And lastly, we point out the limitation of current methods and the unmet needs for better quality control of metagenomic analysis. We hope the information provided here will help investigators in this exciting field to advance their studies while avoiding experimental artifacts.},
}

RevDate: 2018-11-13CmpDate: 2018-11-02

Kolde R, Franzosa EA, Rahnavard G, et al (2018)

Host genetic variation and its microbiome interactions within the Human Microbiome Project.

Genome medicine, 10(1):6 pii:10.1186/s13073-018-0515-8.

BACKGROUND: Despite the increasing recognition that microbial communities within the human body are linked to health, we have an incomplete understanding of the environmental and molecular interactions that shape the composition of these communities. Although host genetic factors play a role in these interactions, these factors have remained relatively unexplored given the requirement for large population-based cohorts in which both genotyping and microbiome characterization have been performed.

METHODS: We performed whole-genome sequencing of 298 donors from the Human Microbiome Project (HMP) healthy cohort study to accompany existing deep characterization of their microbiomes at various body sites. This analysis yielded an average sequencing depth of 32x, with which we identified 27 million (M) single nucleotide variants and 2.3 M insertions-deletions.

RESULTS: Taxonomic composition and functional potential of the microbiome covaried significantly with genetic principal components in the gastrointestinal tract and oral communities, but not in the nares or vaginal microbiota. Example associations included validation of known associations between FUT2 secretor status, as well as a variant conferring hypolactasia near the LCT gene, with Bifidobacterium longum abundance in stool. The associations of microbial features with both high-level genetic attributes and single variants were specific to particular body sites, highlighting the opportunity to find unique genetic mechanisms controlling microbiome properties in the microbial communities from multiple body sites.

CONCLUSIONS: This study adds deep sequencing of host genomes to the body-wide microbiome sequences already extant from the HMP healthy cohort, creating a unique, versatile, and well-controlled reference for future studies seeking to identify host genetic modulators of the microbiome.

METHODS: We performed whole-genome sequencing of 298 donors from the Human Microbiome Project (HMP) healthy cohort study to accompany existing deep characterization of their microbiomes at various body sites. This analysis yielded an average sequencing depth of 32x, with which we identified 27 million (M) single nucleotide variants and 2.3 M insertions-deletions.

RESULTS: Taxonomic composition and functional potential of the microbiome covaried significantly with genetic principal components in the gastrointestinal tract and oral communities, but not in the nares or vaginal microbiota. Example associations included validation of known associations between FUT2 secretor status, as well as a variant conferring hypolactasia near the LCT gene, with Bifidobacterium longum abundance in stool. The associations of microbial features with both high-level genetic attributes and single variants were specific to particular body sites, highlighting the opportunity to find unique genetic mechanisms controlling microbiome properties in the microbial communities from multiple body sites.

BACKGROUND: Most of our knowledge about the remarkable microbial diversity on Earth comes from sequencing the 16S rRNA gene. The use of next-generation sequencing methods has increased sample number and sequencing depth, but the read length of the most widely used sequencing platforms today is quite short, requiring the researcher to choose a subset of the gene to sequence (typically 16-33% of the total length). Thus, many bacteria may share the same amplified region, and the resolution of profiling is inherently limited. Platforms that offer ultra-long read lengths, whole genome shotgun sequencing approaches, and computational frameworks formerly suggested by us and by others all allow different ways to circumvent this problem yet suffer various shortcomings. There is a need for a simple and low-cost 16S rRNA gene-based profiling approach that harnesses the short read length to provide a much larger coverage of the gene to allow for high resolution, even in harsh conditions of low bacterial biomass and fragmented DNA.

RESULTS: This manuscript suggests Short MUltiple Regions Framework (SMURF), a method to combine sequencing results from different PCR-amplified regions to provide one coherent profiling. The de facto amplicon length is the total length of all amplified regions, thus providing much higher resolution compared to current techniques. Computationally, the method solves a convex optimization problem that allows extremely fast reconstruction and requires only moderate memory. We demonstrate the increase in resolution by in silico simulations and by profiling two mock mixtures and real-world biological samples. Reanalyzing a mock mixture from the Human Microbiome Project achieved about twofold improvement in resolution when combing two independent regions. Using a custom set of six primer pairs spanning about 1200 bp (80%) of the 16S rRNA gene, we were able to achieve ~ 100-fold improvement in resolution compared to a single region, over a mock mixture of common human gut bacterial isolates. Finally, the profiling of a Drosophila melanogaster microbiome using the set of six primer pairs provided a ~ 100-fold increase in resolution and thus enabling efficient downstream analysis.

CONCLUSIONS: SMURF enables the identification of near full-length 16S rRNA gene sequences in microbial communities, having resolution superior compared to current techniques. It may be applied to standard sample preparation protocols with very little modifications. SMURF also paves the way to high-resolution profiling of low-biomass and fragmented DNA, e.g., in the case of formalin-fixed and paraffin-embedded samples, fossil-derived DNA, or DNA exposed to other degrading conditions. The approach is not restricted to combining amplicons of the 16S rRNA gene and may be applied to any set of amplicons, e.g., in multilocus sequence typing (MLST).

@article {pmid29373999,
year = {2018},
author = {Fuks, G and Elgart, M and Amir, A and Zeisel, A and Turnbaugh, PJ and Soen, Y and Shental, N},
title = {Combining 16S rRNA gene variable regions enables high-resolution microbial community profiling.},
journal = {Microbiome},
volume = {6},
number = {1},
pages = {17},
doi = {10.1186/s40168-017-0396-x},
pmid = {29373999},
issn = {2049-2618},
support = {R01 HL122593/HL/NHLBI NIH HHS/United States ; 3-11174//Ministry of Science and Technology, Israel/International ; },
mesh = {Algorithms ; Animals ; Bacteria/classification ; Computer Simulation ; DNA Probes/genetics ; DNA, Bacterial/genetics ; Drosophila melanogaster/*microbiology ; Microbiota ; Phylogeny ; Polymerase Chain Reaction/*methods ; RNA, Ribosomal, 16S/*genetics ; Sequence Analysis, DNA/*methods ; },
abstract = {BACKGROUND: Most of our knowledge about the remarkable microbial diversity on Earth comes from sequencing the 16S rRNA gene. The use of next-generation sequencing methods has increased sample number and sequencing depth, but the read length of the most widely used sequencing platforms today is quite short, requiring the researcher to choose a subset of the gene to sequence (typically 16-33% of the total length). Thus, many bacteria may share the same amplified region, and the resolution of profiling is inherently limited. Platforms that offer ultra-long read lengths, whole genome shotgun sequencing approaches, and computational frameworks formerly suggested by us and by others all allow different ways to circumvent this problem yet suffer various shortcomings. There is a need for a simple and low-cost 16S rRNA gene-based profiling approach that harnesses the short read length to provide a much larger coverage of the gene to allow for high resolution, even in harsh conditions of low bacterial biomass and fragmented DNA.

RESULTS: This manuscript suggests Short MUltiple Regions Framework (SMURF), a method to combine sequencing results from different PCR-amplified regions to provide one coherent profiling. The de facto amplicon length is the total length of all amplified regions, thus providing much higher resolution compared to current techniques. Computationally, the method solves a convex optimization problem that allows extremely fast reconstruction and requires only moderate memory. We demonstrate the increase in resolution by in silico simulations and by profiling two mock mixtures and real-world biological samples. Reanalyzing a mock mixture from the Human Microbiome Project achieved about twofold improvement in resolution when combing two independent regions. Using a custom set of six primer pairs spanning about 1200 bp (80%) of the 16S rRNA gene, we were able to achieve ~ 100-fold improvement in resolution compared to a single region, over a mock mixture of common human gut bacterial isolates. Finally, the profiling of a Drosophila melanogaster microbiome using the set of six primer pairs provided a ~ 100-fold increase in resolution and thus enabling efficient downstream analysis.

CONCLUSIONS: SMURF enables the identification of near full-length 16S rRNA gene sequences in microbial communities, having resolution superior compared to current techniques. It may be applied to standard sample preparation protocols with very little modifications. SMURF also paves the way to high-resolution profiling of low-biomass and fragmented DNA, e.g., in the case of formalin-fixed and paraffin-embedded samples, fossil-derived DNA, or DNA exposed to other degrading conditions. The approach is not restricted to combining amplicons of the 16S rRNA gene and may be applied to any set of amplicons, e.g., in multilocus sequence typing (MLST).},
}

Microbiome studies show altered microbiota in head and neck squamous cell carcinoma (HNSCC), both in terms of taxonomic composition and metabolic capacity. These studies utilized a traditional bioinformatics methodology, which allows for accurate taxonomic assignment down to the genus level, but cannot accurately resolve species level membership. We applied Resphera Insight, a high-resolution methodology for 16S rRNA taxonomic assignment that is able to provide species-level context in its assignments of 16S rRNA next generation sequencing (NGS) data. Resphera Insight applied to saliva samples from HNSCC patients and healthy controls led to the discovery that a subset of HNSCC saliva samples is significantly enriched with commensal species from the vaginal flora, including Lactobacillus gasseri/johnsonii (710x higher in saliva) and Lactobacillus vaginalis (52x higher in saliva). These species were not observed in normal saliva from Johns Hopkins patients, nor in 16S rRNA NGS saliva samples from the Human Microbiome Project (HMP). Interestingly, both species were only observed in saliva from Human Papilloma Virus (HPV) positive and HPV negative oropharyngeal cancer patients. We confirmed the representation of both species in HMP data obtained from mid-vagina (n=128) and vaginal introitus (n=121) samples. Resphera Insight also led to the discovery that Fusobacterium nucleatum, an oral cavity flora commensal bacterium linked to colon cancer, is enriched (600x higher) in saliva from a subset of HNSCC patients with advanced tumors stages. Together, these high-resolution analyses on 583 samples suggest a possible role for bacterial species in the therapeutic outcome of HPV positive and HPV negative HNSCC patients.

@article {pmid29340028,
year = {2017},
author = {Guerrero-Preston, R and White, JR and Godoy-Vitorino, F and Rodríguez-Hilario, A and Navarro, K and González, H and Michailidi, C and Jedlicka, A and Canapp, S and Bondy, J and Dziedzic, A and Mora-Lagos, B and Rivera-Alvarez, G and Ili-Gangas, C and Brebi-Mieville, P and Westra, W and Koch, W and Kang, H and Marchionni, L and Kim, Y and Sidransky, D},
title = {High-resolution microbiome profiling uncovers Fusobacterium nucleatum, Lactobacillus gasseri/johnsonii, and Lactobacillus vaginalis associated to oral and oropharyngeal cancer in saliva from HPV positive and HPV negative patients treated with surgery and chemo-radiation.},
journal = {Oncotarget},
volume = {8},
number = {67},
pages = {110931-110948},
doi = {10.18632/oncotarget.20677},
pmid = {29340028},
issn = {1949-2553},
support = {P20 GM103475/GM/NIGMS NIH HHS/United States ; R01 CA121113/CA/NCI NIH HHS/United States ; K01 CA164092/CA/NCI NIH HHS/United States ; P50 DE019032/DE/NIDCR NIH HHS/United States ; RC2 DE020957/DE/NIDCR NIH HHS/United States ; U01 CA084986/CA/NCI NIH HHS/United States ; },
abstract = {Microbiome studies show altered microbiota in head and neck squamous cell carcinoma (HNSCC), both in terms of taxonomic composition and metabolic capacity. These studies utilized a traditional bioinformatics methodology, which allows for accurate taxonomic assignment down to the genus level, but cannot accurately resolve species level membership. We applied Resphera Insight, a high-resolution methodology for 16S rRNA taxonomic assignment that is able to provide species-level context in its assignments of 16S rRNA next generation sequencing (NGS) data. Resphera Insight applied to saliva samples from HNSCC patients and healthy controls led to the discovery that a subset of HNSCC saliva samples is significantly enriched with commensal species from the vaginal flora, including Lactobacillus gasseri/johnsonii (710x higher in saliva) and Lactobacillus vaginalis (52x higher in saliva). These species were not observed in normal saliva from Johns Hopkins patients, nor in 16S rRNA NGS saliva samples from the Human Microbiome Project (HMP). Interestingly, both species were only observed in saliva from Human Papilloma Virus (HPV) positive and HPV negative oropharyngeal cancer patients. We confirmed the representation of both species in HMP data obtained from mid-vagina (n=128) and vaginal introitus (n=121) samples. Resphera Insight also led to the discovery that Fusobacterium nucleatum, an oral cavity flora commensal bacterium linked to colon cancer, is enriched (600x higher) in saliva from a subset of HNSCC patients with advanced tumors stages. Together, these high-resolution analyses on 583 samples suggest a possible role for bacterial species in the therapeutic outcome of HPV positive and HPV negative HNSCC patients.},
}

RevDate: 2018-11-13

Schirmer M, Franzosa EA, Lloyd-Price J, et al (2018)

Dynamics of metatranscription in the inflammatory bowel disease gut microbiome.

Nature microbiology, 3(3):337-346.

Inflammatory bowel disease (IBD) is a group of chronic diseases of the digestive tract that affects millions of people worldwide. Genetic, environmental and microbial factors have been implicated in the onset and exacerbation of IBD. However, the mechanisms associating gut microbial dysbioses and aberrant immune responses remain largely unknown. The integrative Human Microbiome Project seeks to close these gaps by examining the dynamics of microbiome functionality in disease by profiling the gut microbiomes of >100 individuals sampled over a 1-year period. Here, we present the first results based on 78 paired faecal metagenomes and metatranscriptomes, and 222 additional metagenomes from 59 patients with Crohn's disease, 34 with ulcerative colitis and 24 non-IBD control patients. We demonstrate several cases in which measures of microbial gene expression in the inflamed gut can be informative relative to metagenomic profiles of functional potential. First, although many microbial organisms exhibited concordant DNA and RNA abundances, we also detected species-specific biases in transcriptional activity, revealing predominant transcription of pathways by individual microorganisms per host (for example, by Faecalibacterium prausnitzii). Thus, a loss of these organisms in disease may have more far-reaching consequences than suggested by their genomic abundances. Furthermore, we identified organisms that were metagenomically abundant but inactive or dormant in the gut with little or no expression (for example, Dialister invisus). Last, certain disease-specific microbial characteristics were more pronounced or only detectable at the transcript level, such as pathways that were predominantly expressed by different organisms in patients with IBD (for example, Bacteroides vulgatus and Alistipes putredinis). This provides potential insights into gut microbial pathway transcription that can vary over time, inducing phenotypical changes that are complementary to those linked to metagenomic abundances. The study's results highlight the strength of analysing both the activity and the presence of gut microorganisms to provide insight into the role of the microbiome in IBD.

@article {pmid29311644,
year = {2018},
author = {Schirmer, M and Franzosa, EA and Lloyd-Price, J and McIver, LJ and Schwager, R and Poon, TW and Ananthakrishnan, AN and Andrews, E and Barron, G and Lake, K and Prasad, M and Sauk, J and Stevens, B and Wilson, RG and Braun, J and Denson, LA and Kugathasan, S and McGovern, DPB and Vlamakis, H and Xavier, RJ and Huttenhower, C},
title = {Dynamics of metatranscription in the inflammatory bowel disease gut microbiome.},
journal = {Nature microbiology},
volume = {3},
number = {3},
pages = {337-346},
doi = {10.1038/s41564-017-0089-z},
pmid = {29311644},
issn = {2058-5276},
support = {U54 DK102557/DK/NIDDK NIH HHS/United States ; U01 DK062413/DK/NIDDK NIH HHS/United States ; P30 DK043351/DK/NIDDK NIH HHS/United States ; R01 DK092405/DK/NIDDK NIH HHS/United States ; P01 DK046763/DK/NIDDK NIH HHS/United States ; UL1 TR001881/TR/NCATS NIH HHS/United States ; },
abstract = {Inflammatory bowel disease (IBD) is a group of chronic diseases of the digestive tract that affects millions of people worldwide. Genetic, environmental and microbial factors have been implicated in the onset and exacerbation of IBD. However, the mechanisms associating gut microbial dysbioses and aberrant immune responses remain largely unknown. The integrative Human Microbiome Project seeks to close these gaps by examining the dynamics of microbiome functionality in disease by profiling the gut microbiomes of >100 individuals sampled over a 1-year period. Here, we present the first results based on 78 paired faecal metagenomes and metatranscriptomes, and 222 additional metagenomes from 59 patients with Crohn's disease, 34 with ulcerative colitis and 24 non-IBD control patients. We demonstrate several cases in which measures of microbial gene expression in the inflamed gut can be informative relative to metagenomic profiles of functional potential. First, although many microbial organisms exhibited concordant DNA and RNA abundances, we also detected species-specific biases in transcriptional activity, revealing predominant transcription of pathways by individual microorganisms per host (for example, by Faecalibacterium prausnitzii). Thus, a loss of these organisms in disease may have more far-reaching consequences than suggested by their genomic abundances. Furthermore, we identified organisms that were metagenomically abundant but inactive or dormant in the gut with little or no expression (for example, Dialister invisus). Last, certain disease-specific microbial characteristics were more pronounced or only detectable at the transcript level, such as pathways that were predominantly expressed by different organisms in patients with IBD (for example, Bacteroides vulgatus and Alistipes putredinis). This provides potential insights into gut microbial pathway transcription that can vary over time, inducing phenotypical changes that are complementary to those linked to metagenomic abundances. The study's results highlight the strength of analysing both the activity and the presence of gut microorganisms to provide insight into the role of the microbiome in IBD.},
}

Due to the recent advances in high-throughput sequencing technologies, it becomes possible to directly analyze microbial communities in human body and environment. To understand how microbial communities adapt, develop, and interact with the human body and the surrounding environment, one of the fundamental challenges is to infer the interactions among different microbes. However, due to the compositional and high-dimensional nature of microbial data, statistical inference cannot offer reliable results. Consequently, new approaches that can accurately and robustly estimate the associations (putative interactions) among microbes are needed to analyze such compositional and high-dimensional data. We propose a novel framework called Microbial Prior Lasso (MPLasso) which integrates graph learning algorithm with microbial co-occurrences and associations obtained from scientific literature by using automated text mining. We show that MPLasso outperforms existing models in terms of accuracy, microbial network recovery rate, and reproducibility. Furthermore, the association networks we obtain from the Human Microbiome Project datasets show credible results when compared against laboratory data.

Thanks in large part to newer, better, and cheaper DNA sequencing technologies, an enormous number of metagenomic sequence datasets have been and continue to be generated, covering a huge variety of environmental niches, including several different human body sites. Comparing these metagenomes and identifying their commonalities and differences is a challenging task, due not only to the large amounts of data, but also because there are several methodological considerations that need to be taken into account to ensure an appropriate and sound comparison between datasets. In this chapter, we describe current techniques aimed at comparing metagenomes generated by 16S ribosomal RNA and shotgun DNA sequencing, emphasizing methodological issues that arise in these comparative studies. We provide a detailed case study to illustrate some of these techniques using data from the Human Microbiome Project comparing the microbial communities from ten buccal mucosa samples with ten tongue dorsum samples in terms of alpha diversity, beta diversity, and their taxonomic and functional profiles.

@article {pmid29277868,
year = {2018},
author = {Maltez Thomas, A and Prata Lima, F and Maria Silva Moura, L and Maria da Silva, A and Dias-Neto, E and Setubal, JC},
title = {Comparative Metagenomics.},
journal = {Methods in molecular biology (Clifton, N.J.)},
volume = {1704},
number = {},
pages = {243-260},
doi = {10.1007/978-1-4939-7463-4_8},
pmid = {29277868},
issn = {1940-6029},
abstract = {Thanks in large part to newer, better, and cheaper DNA sequencing technologies, an enormous number of metagenomic sequence datasets have been and continue to be generated, covering a huge variety of environmental niches, including several different human body sites. Comparing these metagenomes and identifying their commonalities and differences is a challenging task, due not only to the large amounts of data, but also because there are several methodological considerations that need to be taken into account to ensure an appropriate and sound comparison between datasets. In this chapter, we describe current techniques aimed at comparing metagenomes generated by 16S ribosomal RNA and shotgun DNA sequencing, emphasizing methodological issues that arise in these comparative studies. We provide a detailed case study to illustrate some of these techniques using data from the Human Microbiome Project comparing the microbial communities from ten buccal mucosa samples with ten tongue dorsum samples in terms of alpha diversity, beta diversity, and their taxonomic and functional profiles.},
}

RevDate: 2018-11-13

Huang L, Krüger J, A Sczyrba (2018)

Analyzing large scale genomic data on the cloud with Sparkhit.

Bioinformatics (Oxford, England), 34(9):1457-1465.

Motivation: The increasing amount of next-generation sequencing data poses a fundamental challenge on large scale genomic analytics. Existing tools use different distributed computational platforms to scale-out bioinformatics workloads. However, the scalability of these tools is not efficient. Moreover, they have heavy run time overheads when pre-processing large amounts of data. To address these limitations, we have developed Sparkhit: a distributed bioinformatics framework built on top of the Apache Spark platform.

Results: Sparkhit integrates a variety of analytical methods. It is implemented in the Spark extended MapReduce model. It runs 92-157 times faster than MetaSpark on metagenomic fragment recruitment and 18-32 times faster than Crossbow on data pre-processing. We analyzed 100 terabytes of data across four genomic projects in the cloud in 21 h, which includes the run times of cluster deployment and data downloading. Furthermore, our application on the entire Human Microbiome Project shotgun sequencing data was completed in 2 h, presenting an approach to easily associate large amounts of public datasets with reference data.

Sparkhit is freely available at: https://rhinempi.github.io/sparkhit/.

Contact: asczyrba@cebitec.uni-bielefeld.de.

Supplementary information: Supplementary data are available at Bioinformatics online.

@article {pmid29253074,
year = {2018},
author = {Huang, L and Krüger, J and Sczyrba, A},
title = {Analyzing large scale genomic data on the cloud with Sparkhit.},
journal = {Bioinformatics (Oxford, England)},
volume = {34},
number = {9},
pages = {1457-1465},
doi = {10.1093/bioinformatics/btx808},
pmid = {29253074},
issn = {1367-4811},
abstract = {Motivation: The increasing amount of next-generation sequencing data poses a fundamental challenge on large scale genomic analytics. Existing tools use different distributed computational platforms to scale-out bioinformatics workloads. However, the scalability of these tools is not efficient. Moreover, they have heavy run time overheads when pre-processing large amounts of data. To address these limitations, we have developed Sparkhit: a distributed bioinformatics framework built on top of the Apache Spark platform.

Results: Sparkhit integrates a variety of analytical methods. It is implemented in the Spark extended MapReduce model. It runs 92-157 times faster than MetaSpark on metagenomic fragment recruitment and 18-32 times faster than Crossbow on data pre-processing. We analyzed 100 terabytes of data across four genomic projects in the cloud in 21 h, which includes the run times of cluster deployment and data downloading. Furthermore, our application on the entire Human Microbiome Project shotgun sequencing data was completed in 2 h, presenting an approach to easily associate large amounts of public datasets with reference data.

Sparkhit is freely available at: https://rhinempi.github.io/sparkhit/.

Contact: asczyrba@cebitec.uni-bielefeld.de.

Supplementary information: Supplementary data are available at Bioinformatics online.},
}

Immune defence against pathogenic agents comprises the basic premise for the administration of vaccines. Vaccinations have hence prevented millions of infectious illnesses, hospitalizations and mortality. Acquired immunity comprises antibody and cell mediated responses and is characterized by its specificity and memory. Along a similar congruent yet diverse mode of disease prevention, the human host has negotiated from in utero and at birth with the intestinal commensal bacterial cohort to maintain local homeostasis in order to achieve immunological tolerance in the new born. The advent of the Human Microbiome Project has redefined an appreciation of the interactions between the host and bacteria in the intestines from one of a collection of toxic waste to one of a symbiotic existence. Probiotics comprise bacterial genera thought to provide a health benefit to the host. The intestinal microbiota has profound effects on local and extra-intestinal end organ physiology. As such, we further posit that the adjuvant administration of dedicated probiotic formulations can encourage the intestinal commensal cohort to beneficially participate in the intestinal microbiome-intestinal epithelia-innate-cell mediated immunity axes and cell mediated cellular immunity with vaccines aimed at preventing infectious diseases whilst conserving immunological tolerance. The strength of evidence for the positive effect of probiotic administration on acquired immune responses has come from various studies with viral and bacterial vaccines. We posit that the introduction early of probiotics may provide significant beneficial immune outcomes in neonates prior to commencing a vaccination schedule or in elderly adults prior to the administration of vaccinations against influenza viruses.

@article {pmid29232932,
year = {2017},
author = {Vitetta, L and Saltzman, ET and Thomsen, M and Nikov, T and Hall, S},
title = {Adjuvant Probiotics and the Intestinal Microbiome: Enhancing Vaccines and Immunotherapy Outcomes.},
journal = {Vaccines},
volume = {5},
number = {4},
pages = {},
doi = {10.3390/vaccines5040050},
pmid = {29232932},
issn = {2076-393X},
abstract = {Immune defence against pathogenic agents comprises the basic premise for the administration of vaccines. Vaccinations have hence prevented millions of infectious illnesses, hospitalizations and mortality. Acquired immunity comprises antibody and cell mediated responses and is characterized by its specificity and memory. Along a similar congruent yet diverse mode of disease prevention, the human host has negotiated from in utero and at birth with the intestinal commensal bacterial cohort to maintain local homeostasis in order to achieve immunological tolerance in the new born. The advent of the Human Microbiome Project has redefined an appreciation of the interactions between the host and bacteria in the intestines from one of a collection of toxic waste to one of a symbiotic existence. Probiotics comprise bacterial genera thought to provide a health benefit to the host. The intestinal microbiota has profound effects on local and extra-intestinal end organ physiology. As such, we further posit that the adjuvant administration of dedicated probiotic formulations can encourage the intestinal commensal cohort to beneficially participate in the intestinal microbiome-intestinal epithelia-innate-cell mediated immunity axes and cell mediated cellular immunity with vaccines aimed at preventing infectious diseases whilst conserving immunological tolerance. The strength of evidence for the positive effect of probiotic administration on acquired immune responses has come from various studies with viral and bacterial vaccines. We posit that the introduction early of probiotics may provide significant beneficial immune outcomes in neonates prior to commencing a vaccination schedule or in elderly adults prior to the administration of vaccinations against influenza viruses.},
}

RevDate: 2018-07-24CmpDate: 2018-07-24

Moffatt MF, WO Cookson (2017)

The lung microbiome in health and disease.

Clinical medicine (London, England), 17(6):525-529.

The Human Microbiome Project began 10 years ago, leading to a significant growth in understanding of the role the human microbiome plays in health and disease. In this article, we explain with an emphasis on the lung, the origins of microbiome research. We discuss how 16S rRNA gene sequencing became the first major molecular tool to examine the bacterial communities present within the human body. We highlight the pitfalls of molecular-based studies, such as false findings resulting from contamination, and the limitations of 16S rRNA gene sequencing. Knowledge about the lung microbiome has evolved from initial scepticism to the realisation that it might have a significant influence on many illnesses. We also discuss the lung microbiome in the context of disease by giving examples of important respiratory conditions. In addition, we draw attention to the challenges for metagenomic studies of respiratory samples and the importance of systematic bacterial isolation to enable host-microbiome interactions to be understood. We conclude by discussing how knowledge of the lung microbiome impacts current clinical diagnostics.

@article {pmid29196353,
year = {2017},
author = {Moffatt, MF and Cookson, WO},
title = {The lung microbiome in health and disease.},
journal = {Clinical medicine (London, England)},
volume = {17},
number = {6},
pages = {525-529},
doi = {10.7861/clinmedicine.17-6-525},
pmid = {29196353},
issn = {1473-4893},
mesh = {Asthma/microbiology ; Bronchiectasis/microbiology ; Cystic Fibrosis/microbiology ; Humans ; Lung/*microbiology ; Lung Diseases/*microbiology ; Metagenomics ; *Microbiota/genetics ; Pulmonary Disease, Chronic Obstructive/microbiology ; RNA, Ribosomal, 16S/genetics ; },
abstract = {The Human Microbiome Project began 10 years ago, leading to a significant growth in understanding of the role the human microbiome plays in health and disease. In this article, we explain with an emphasis on the lung, the origins of microbiome research. We discuss how 16S rRNA gene sequencing became the first major molecular tool to examine the bacterial communities present within the human body. We highlight the pitfalls of molecular-based studies, such as false findings resulting from contamination, and the limitations of 16S rRNA gene sequencing. Knowledge about the lung microbiome has evolved from initial scepticism to the realisation that it might have a significant influence on many illnesses. We also discuss the lung microbiome in the context of disease by giving examples of important respiratory conditions. In addition, we draw attention to the challenges for metagenomic studies of respiratory samples and the importance of systematic bacterial isolation to enable host-microbiome interactions to be understood. We conclude by discussing how knowledge of the lung microbiome impacts current clinical diagnostics.},
}

BACKGROUND: Most studies describing the human gut microbiome in healthy and diseased states have emphasized the bacterial component, but the fungal microbiome (i.e., the mycobiome) is beginning to gain recognition as a fundamental part of our microbiome. To date, human gut mycobiome studies have primarily been disease centric or in small cohorts of healthy individuals. To contribute to existing knowledge of the human mycobiome, we investigated the gut mycobiome of the Human Microbiome Project (HMP) cohort by sequencing the Internal Transcribed Spacer 2 (ITS2) region as well as the 18S rRNA gene.

RESULTS: Three hundred seventeen HMP stool samples were analyzed by ITS2 sequencing. Fecal fungal diversity was significantly lower in comparison to bacterial diversity. Yeast dominated the samples, comprising eight of the top 15 most abundant genera. Specifically, fungal communities were characterized by a high prevalence of Saccharomyces, Malassezia, and Candida, with S. cerevisiae, M. restricta, and C. albicans operational taxonomic units (OTUs) present in 96.8, 88.3, and 80.8% of samples, respectively. There was a high degree of inter- and intra-volunteer variability in fungal communities. However, S. cerevisiae, M. restricta, and C. albicans OTUs were found in 92.2, 78.3, and 63.6% of volunteers, respectively, in all samples donated over an approximately 1-year period. Metagenomic and 18S rRNA gene sequencing data agreed with ITS2 results; however, ITS2 sequencing provided greater resolution of the relatively low abundance mycobiome constituents.

CONCLUSIONS: Compared to bacterial communities, the human gut mycobiome is low in diversity and dominated by yeast including Saccharomyces, Malassezia, and Candida. Both inter- and intra-volunteer variability in the HMP cohort were high, revealing that unlike bacterial communities, an individual's mycobiome is no more similar to itself over time than to another person's. Nonetheless, several fungal species persisted across a majority of samples, evidence that a core gut mycobiome may exist. ITS2 sequencing data provided greater resolution of the mycobiome membership compared to metagenomic and 18S rRNA gene sequencing data, suggesting that it is a more sensitive method for studying the mycobiome of stool samples.

RESULTS: Three hundred seventeen HMP stool samples were analyzed by ITS2 sequencing. Fecal fungal diversity was significantly lower in comparison to bacterial diversity. Yeast dominated the samples, comprising eight of the top 15 most abundant genera. Specifically, fungal communities were characterized by a high prevalence of Saccharomyces, Malassezia, and Candida, with S. cerevisiae, M. restricta, and C. albicans operational taxonomic units (OTUs) present in 96.8, 88.3, and 80.8% of samples, respectively. There was a high degree of inter- and intra-volunteer variability in fungal communities. However, S. cerevisiae, M. restricta, and C. albicans OTUs were found in 92.2, 78.3, and 63.6% of volunteers, respectively, in all samples donated over an approximately 1-year period. Metagenomic and 18S rRNA gene sequencing data agreed with ITS2 results; however, ITS2 sequencing provided greater resolution of the relatively low abundance mycobiome constituents.

CONCLUSIONS: Compared to bacterial communities, the human gut mycobiome is low in diversity and dominated by yeast including Saccharomyces, Malassezia, and Candida. Both inter- and intra-volunteer variability in the HMP cohort were high, revealing that unlike bacterial communities, an individual's mycobiome is no more similar to itself over time than to another person's. Nonetheless, several fungal species persisted across a majority of samples, evidence that a core gut mycobiome may exist. ITS2 sequencing data provided greater resolution of the mycobiome membership compared to metagenomic and 18S rRNA gene sequencing data, suggesting that it is a more sensitive method for studying the mycobiome of stool samples.},
}

Motivation. Microbiome sequencing allows defining clusters of samples with shared composition. However, this paradigm poorly accounts for samples whose composition is a mixture of cluster-characterizing ones and which therefore lie in between them in the cluster space. This paper addresses unsupervised learning of 2-way clusters. It defines a mixture model that allows 2-way cluster assignment and describes a variant of generalized k-means for learning such a model. We demonstrate applicability to microbial 16S rDNA sequencing data from the Human Vaginal Microbiome Project.

Cohabitation of microbial communities with the host enables the formation of a symbiotic relationship that maintains homeostasis in the gut and beyond. One prevailing model suggests that this relationship relies on the capacity of host cells and tissues to remain tolerant to the strong immune stimulation generated by the microbiota such as the activation of Toll-like receptor 4 (TLR4) pathways by lipopolysaccharide (LPS). Indeed, gut microbial LPS is thought to be one of the most potent activators of innate immune signaling and an important mediator of the microbiome's influence on host physiology. In this study, we performed computational and experimental analyses of healthy human fecal samples to examine the TLR4 signaling capacity of the gut microbiota. These analyses revealed that an immunoinhibitory activity of LPS, conserved across the members of the order Bacteroidales and derived from an underacylated structural feature, silences TLR4 signaling for the entire consortium of organisms inhabiting the human gut. Comparative analysis of metagenomic data from the Human Microbiome Project and healthy-donor samples indicates that immune silencing via LPS is a microbe-intrinsic feature in all healthy adults. These findings challenge the current belief that robust TLR4 signaling is a feature of the microbiome and demonstrate that microbiome-derived LPS has the ability to facilitate host tolerance of gut microbes. These findings have broad implications for how we model host-microbe interactions and for our understanding of microbiome-linked disease. IMPORTANCE While the ability for humans to host a complex microbial ecosystem is an essential property of life, the mechanisms allowing for immune tolerance of such a large microbial load are not completely understood and are currently the focus of intense research. This study shows that an important proinflammatory pathway that is commonly triggered by pathogenic bacteria upon interaction with the host is, in fact, actively repressed by the bacteria of the gut microbiome, supporting the idea that beneficial microbes themselves contribute to the immune tolerance in support of homeostasis. These findings are important for two reasons. First, many currently assume that proinflammatory signaling by lipopolysaccharide is a fundamental feature of the gut flora. This assumption influences greatly how host-microbiome interactions are theoretically modeled but also how they are experimentally studied, by using robust TLR signaling conditions to simulate commensals. Second, elucidation of the mechanisms that support host-microbe tolerance is key to the development of therapeutics for both intestinal and systemic inflammatory disorders.

@article {pmid29152585,
year = {2017},
author = {d'Hennezel, E and Abubucker, S and Murphy, LO and Cullen, TW},
title = {Total Lipopolysaccharide from the Human Gut Microbiome Silences Toll-Like Receptor Signaling.},
journal = {mSystems},
volume = {2},
number = {6},
pages = {},
doi = {10.1128/mSystems.00046-17},
pmid = {29152585},
issn = {2379-5077},
abstract = {Cohabitation of microbial communities with the host enables the formation of a symbiotic relationship that maintains homeostasis in the gut and beyond. One prevailing model suggests that this relationship relies on the capacity of host cells and tissues to remain tolerant to the strong immune stimulation generated by the microbiota such as the activation of Toll-like receptor 4 (TLR4) pathways by lipopolysaccharide (LPS). Indeed, gut microbial LPS is thought to be one of the most potent activators of innate immune signaling and an important mediator of the microbiome's influence on host physiology. In this study, we performed computational and experimental analyses of healthy human fecal samples to examine the TLR4 signaling capacity of the gut microbiota. These analyses revealed that an immunoinhibitory activity of LPS, conserved across the members of the order Bacteroidales and derived from an underacylated structural feature, silences TLR4 signaling for the entire consortium of organisms inhabiting the human gut. Comparative analysis of metagenomic data from the Human Microbiome Project and healthy-donor samples indicates that immune silencing via LPS is a microbe-intrinsic feature in all healthy adults. These findings challenge the current belief that robust TLR4 signaling is a feature of the microbiome and demonstrate that microbiome-derived LPS has the ability to facilitate host tolerance of gut microbes. These findings have broad implications for how we model host-microbe interactions and for our understanding of microbiome-linked disease. IMPORTANCE While the ability for humans to host a complex microbial ecosystem is an essential property of life, the mechanisms allowing for immune tolerance of such a large microbial load are not completely understood and are currently the focus of intense research. This study shows that an important proinflammatory pathway that is commonly triggered by pathogenic bacteria upon interaction with the host is, in fact, actively repressed by the bacteria of the gut microbiome, supporting the idea that beneficial microbes themselves contribute to the immune tolerance in support of homeostasis. These findings are important for two reasons. First, many currently assume that proinflammatory signaling by lipopolysaccharide is a fundamental feature of the gut flora. This assumption influences greatly how host-microbiome interactions are theoretically modeled but also how they are experimentally studied, by using robust TLR signaling conditions to simulate commensals. Second, elucidation of the mechanisms that support host-microbe tolerance is key to the development of therapeutics for both intestinal and systemic inflammatory disorders.},
}

RevDate: 2018-11-13CmpDate: 2017-12-12

Schwager E, Mallick H, Ventz S, et al (2017)

A Bayesian method for detecting pairwise associations in compositional data.

PLoS computational biology, 13(11):e1005852 pii:PCOMPBIOL-D-17-00827.

Compositional data consist of vectors of proportions normalized to a constant sum from a basis of unobserved counts. The sum constraint makes inference on correlations between unconstrained features challenging due to the information loss from normalization. However, such correlations are of long-standing interest in fields including ecology. We propose a novel Bayesian framework (BAnOCC: Bayesian Analysis of Compositional Covariance) to estimate a sparse precision matrix through a LASSO prior. The resulting posterior, generated by MCMC sampling, allows uncertainty quantification of any function of the precision matrix, including the correlation matrix. We also use a first-order Taylor expansion to approximate the transformation from the unobserved counts to the composition in order to investigate what characteristics of the unobserved counts can make the correlations more or less difficult to infer. On simulated datasets, we show that BAnOCC infers the true network as well as previous methods while offering the advantage of posterior inference. Larger and more realistic simulated datasets further showed that BAnOCC performs well as measured by type I and type II error rates. Finally, we apply BAnOCC to a microbial ecology dataset from the Human Microbiome Project, which in addition to reproducing established ecological results revealed unique, competition-based roles for Proteobacteria in multiple distinct habitats.

@article {pmid29140991,
year = {2017},
author = {Schwager, E and Mallick, H and Ventz, S and Huttenhower, C},
title = {A Bayesian method for detecting pairwise associations in compositional data.},
journal = {PLoS computational biology},
volume = {13},
number = {11},
pages = {e1005852},
doi = {10.1371/journal.pcbi.1005852},
pmid = {29140991},
issn = {1553-7358},
support = {T32 GM074897/GM/NIGMS NIH HHS/United States ; U54 DK102557/DK/NIDDK NIH HHS/United States ; },
mesh = {Algorithms ; *Bayes Theorem ; Computational Biology/*methods ; *Computer Simulation ; Ecology ; Humans ; Markov Chains ; Microbiota ; *Models, Biological ; Proteobacteria ; },
abstract = {Compositional data consist of vectors of proportions normalized to a constant sum from a basis of unobserved counts. The sum constraint makes inference on correlations between unconstrained features challenging due to the information loss from normalization. However, such correlations are of long-standing interest in fields including ecology. We propose a novel Bayesian framework (BAnOCC: Bayesian Analysis of Compositional Covariance) to estimate a sparse precision matrix through a LASSO prior. The resulting posterior, generated by MCMC sampling, allows uncertainty quantification of any function of the precision matrix, including the correlation matrix. We also use a first-order Taylor expansion to approximate the transformation from the unobserved counts to the composition in order to investigate what characteristics of the unobserved counts can make the correlations more or less difficult to infer. On simulated datasets, we show that BAnOCC infers the true network as well as previous methods while offering the advantage of posterior inference. Larger and more realistic simulated datasets further showed that BAnOCC performs well as measured by type I and type II error rates. Finally, we apply BAnOCC to a microbial ecology dataset from the Human Microbiome Project, which in addition to reproducing established ecological results revealed unique, competition-based roles for Proteobacteria in multiple distinct habitats.},
}

Phylogenic inference using alignment-free methods for applications in microbial community surveys using 16s rRNA gene.

PloS one, 12(11):e0187940 pii:PONE-D-17-12951.

The diversity of microbiota is best explored by understanding the phylogenetic structure of the microbial communities. Traditionally, sequence alignment has been used for phylogenetic inference. However, alignment-based approaches come with significant challenges and limitations when massive amounts of data are analyzed. In the recent decade, alignment-free approaches have enabled genome-scale phylogenetic inference. Here we evaluate three alignment-free methods: ACS, CVTree, and Kr for phylogenetic inference with 16s rRNA gene data. We use a taxonomic gold standard to compare the accuracy of alignment-free phylogenetic inference with that of common microbiome-wide phylogenetic inference pipelines based on PyNAST and MUSCLE alignments with FastTree and RAxML. We re-simulate fecal communities from Human Microbiome Project data to evaluate the performance of the methods on datasets with properties of real data. Our comparisons show that alignment-free methods are not inferior to alignment-based methods in giving accurate and robust phylogenic trees. Moreover, consensus ensembles of alignment-free phylogenies are superior to those built from alignment-based methods in their ability to highlight community differences in low power settings. In addition, the overall running times of alignment-based and alignment-free phylogenetic inference are comparable. Taken together our empirical results suggest that alignment-free methods provide a viable approach for microbiome-wide phylogenetic inference.

@article {pmid29136663,
year = {2017},
author = {Zhang, Y and Alekseyenko, AV},
title = {Phylogenic inference using alignment-free methods for applications in microbial community surveys using 16s rRNA gene.},
journal = {PloS one},
volume = {12},
number = {11},
pages = {e0187940},
doi = {10.1371/journal.pone.0187940},
pmid = {29136663},
issn = {1932-6203},
mesh = {Microbiota/*genetics ; *Phylogeny ; RNA, Ribosomal, 16S/*genetics ; },
abstract = {The diversity of microbiota is best explored by understanding the phylogenetic structure of the microbial communities. Traditionally, sequence alignment has been used for phylogenetic inference. However, alignment-based approaches come with significant challenges and limitations when massive amounts of data are analyzed. In the recent decade, alignment-free approaches have enabled genome-scale phylogenetic inference. Here we evaluate three alignment-free methods: ACS, CVTree, and Kr for phylogenetic inference with 16s rRNA gene data. We use a taxonomic gold standard to compare the accuracy of alignment-free phylogenetic inference with that of common microbiome-wide phylogenetic inference pipelines based on PyNAST and MUSCLE alignments with FastTree and RAxML. We re-simulate fecal communities from Human Microbiome Project data to evaluate the performance of the methods on datasets with properties of real data. Our comparisons show that alignment-free methods are not inferior to alignment-based methods in giving accurate and robust phylogenic trees. Moreover, consensus ensembles of alignment-free phylogenies are superior to those built from alignment-based methods in their ability to highlight community differences in low power settings. In addition, the overall running times of alignment-based and alignment-free phylogenetic inference are comparable. Taken together our empirical results suggest that alignment-free methods provide a viable approach for microbiome-wide phylogenetic inference.},
}

MeSH Terms:

show MeSH Terms

hide MeSH Terms

Microbiota/*genetics*PhylogenyRNA, Ribosomal, 16S/*genetics

RevDate: 2018-08-22CmpDate: 2018-08-22

Li J, Fu R, Yang Y, et al (2018)

A metagenomic approach to dissect the genetic composition of enterotypes in Han Chinese and two Muslim groups.

Systematic and applied microbiology, 41(1):1-12.

Distinct enterotypes have been observed in the human gut but little is known about the genetic basis of the microbiome. Moreover, it is not clear how many genetic differences exist between enterotypes within or between populations. In this study, both the 16S rRNA gene and the metagenomes of the gut microbiota were sequenced from 48 Han Chinese, 48 Kazaks, and 96 Uyghurs, and taxonomies were assigned after de novo assembly. Single nucleotide polymorphisms were also identified by referring to data from the Human Microbiome Project. Systematic analysis of the gut communities in terms of their abundance and genetic composition was also performed, together with a genome-wide association study of the host genomes. The gut microbiota of 192 subjects was clearly classified into two enterotypes (Bacteroides and Prevotella). Interestingly, both enterotypes showed a clear genetic differentiation in terms of their functional catalogue of genes, especially for genes involved in amino acid and carbohydrate metabolism. In addition, several differentiated genera and genes were found among the three populations. Notably, one human variant (rs878394) was identified that showed significant association with the abundance of Prevotella, which is linked to LYPLAL1, a gene associated with body fat distribution, the waist-hip ratio and insulin sensitivity. Taken together, considerable differentiation was observed in gut microbes between enterotypes and among populations that was reflected in both the taxonomic composition and the genetic makeup of their functional genes, which could have been influenced by a variety of factors, such as diet and host genetic variation.

@article {pmid29129355,
year = {2018},
author = {Li, J and Fu, R and Yang, Y and Horz, HP and Guan, Y and Lu, Y and Lou, H and Tian, L and Zheng, S and Liu, H and Shi, M and Tang, K and Wang, S and Xu, S},
title = {A metagenomic approach to dissect the genetic composition of enterotypes in Han Chinese and two Muslim groups.},
journal = {Systematic and applied microbiology},
volume = {41},
number = {1},
pages = {1-12},
doi = {10.1016/j.syapm.2017.09.006},
pmid = {29129355},
issn = {1618-0984},
mesh = {Asian Continental Ancestry Group ; Bacteria/*classification/*genetics ; Cluster Analysis ; DNA, Bacterial/chemistry/genetics ; DNA, Ribosomal/chemistry/genetics ; Ethnic Groups ; *Gastrointestinal Microbiome ; Genetic Association Studies ; Healthy Volunteers ; Humans ; Islam ; Lysophospholipase/genetics ; *Metagenomics ; *Microbiota ; Phylogeny ; Polymorphism, Single Nucleotide ; RNA, Ribosomal, 16S/genetics ; Sequence Analysis, DNA ; },
abstract = {Distinct enterotypes have been observed in the human gut but little is known about the genetic basis of the microbiome. Moreover, it is not clear how many genetic differences exist between enterotypes within or between populations. In this study, both the 16S rRNA gene and the metagenomes of the gut microbiota were sequenced from 48 Han Chinese, 48 Kazaks, and 96 Uyghurs, and taxonomies were assigned after de novo assembly. Single nucleotide polymorphisms were also identified by referring to data from the Human Microbiome Project. Systematic analysis of the gut communities in terms of their abundance and genetic composition was also performed, together with a genome-wide association study of the host genomes. The gut microbiota of 192 subjects was clearly classified into two enterotypes (Bacteroides and Prevotella). Interestingly, both enterotypes showed a clear genetic differentiation in terms of their functional catalogue of genes, especially for genes involved in amino acid and carbohydrate metabolism. In addition, several differentiated genera and genes were found among the three populations. Notably, one human variant (rs878394) was identified that showed significant association with the abundance of Prevotella, which is linked to LYPLAL1, a gene associated with body fat distribution, the waist-hip ratio and insulin sensitivity. Taken together, considerable differentiation was observed in gut microbes between enterotypes and among populations that was reflected in both the taxonomic composition and the genetic makeup of their functional genes, which could have been influenced by a variety of factors, such as diet and host genetic variation.},
}

BACKGROUND: It is clear that specific intestinal bacteria are involved in the development of different premalignant conditions along the gastrointestinal tract. An analysis of the microbial constituents in the context of pancreatic cystic lesions has, however, as yet not been performed. This consideration prompted us to explore whether endoscopically obtained pancreatic cyst fluids (PCF) contain bacterial DNA and to determine the genera of bacteria present in such material.

METHODS: Total DNA was isolated from 69 PCF samples. Bacterial 16S rRNA gene-specific PCR was performed followed by Sanger sequencing and de novo deep sequencing for the V3-V4 variable region of 16S rRNA gene.

RESULTS: We observed that 98.2% of the samples were positive in conventional PCR, and that 100% of selected PCF samples (n = 33) were positive for bacterial microbiota as determined by next generation sequencing (NGS). Comprehensive NGS data analysis of PCF showed the presence of 408 genera of bacteria, of which 17 bacterial genera were uniquely abundant to PCF, when compared to the Human Microbiome Project (HMP) database and 15 bacterial microbiota were uniquely abundant in HMP only. Bacteroides spp., Escherichia/Shigella spp., and Acidaminococcus spp. which were predominant in PCF, while also a substantial Staphylococcus spp. and Fusobacterium spp. component was detected.

CONCLUSION: These results reveal and characterize an apparently specific bacterial ecosystem in pancreatic cyst fluid samples and may reflect the local microbiota in the pancreas. Some taxa with potential deleterious functions are present in the bacterial abundance profiles, suggesting that the unique microbiome in this specific niche may contribute to neoplastic processes in the pancreas. Further studies are needed to explore the intricate relationship between pathophysiological status in the host pancreas and its microbiota.

METHODS: Total DNA was isolated from 69 PCF samples. Bacterial 16S rRNA gene-specific PCR was performed followed by Sanger sequencing and de novo deep sequencing for the V3-V4 variable region of 16S rRNA gene.

RESULTS: We observed that 98.2% of the samples were positive in conventional PCR, and that 100% of selected PCF samples (n = 33) were positive for bacterial microbiota as determined by next generation sequencing (NGS). Comprehensive NGS data analysis of PCF showed the presence of 408 genera of bacteria, of which 17 bacterial genera were uniquely abundant to PCF, when compared to the Human Microbiome Project (HMP) database and 15 bacterial microbiota were uniquely abundant in HMP only. Bacteroides spp., Escherichia/Shigella spp., and Acidaminococcus spp. which were predominant in PCF, while also a substantial Staphylococcus spp. and Fusobacterium spp. component was detected.

CONCLUSION: These results reveal and characterize an apparently specific bacterial ecosystem in pancreatic cyst fluid samples and may reflect the local microbiota in the pancreas. Some taxa with potential deleterious functions are present in the bacterial abundance profiles, suggesting that the unique microbiome in this specific niche may contribute to neoplastic processes in the pancreas. Further studies are needed to explore the intricate relationship between pathophysiological status in the host pancreas and its microbiota.},
}

MicrobiomeDB (http://microbiomeDB.org) is a data discovery and analysis platform that empowers researchers to fully leverage experimental variables to interrogate microbiome datasets. MicrobiomeDB was developed in collaboration with the Eukaryotic Pathogens Bioinformatics Resource Center (http://EuPathDB.org) and leverages the infrastructure and user interface of EuPathDB, which allows users to construct in silico experiments using an intuitive graphical 'strategy' approach. The current release of the database integrates microbial census data with sample details for nearly 14 000 samples originating from human, animal and environmental sources, including over 9000 samples from healthy human subjects in the Human Microbiome Project (http://portal.ihmpdcc.org/). Query results can be statistically analyzed and graphically visualized via interactive web applications launched directly in the browser, providing insight into microbial community diversity and allowing users to identify taxa associated with any experimental covariate.

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.

Lung diseases caused by microbial infections affect hundreds of millions of children and adults throughout the world. In Western populations, the treatment of lung infections is a primary driver of antibiotic resistance. Traditional therapeutic strategies have been based on the premise that the healthy lung is sterile and that infections grow in a pristine environment. As a consequence, rapid advances in our understanding of the composition of the microbiota of the skin and bowel have not yet been matched by studies of the respiratory tree. The recognition that the lungs are as populated with microorganisms as other mucosal surfaces provides the opportunity to reconsider the mechanisms and management of lung infections. Molecular analyses of the lung microbiota are revealing profound adverse responses to widespread antibiotic use, urbanization and globalization. This Opinion article proposes how technologies and concepts flowing from the Human Microbiome Project can transform the diagnosis and treatment of common lung diseases.

@article {pmid29062070,
year = {2018},
author = {Cookson, WOCM and Cox, MJ and Moffatt, MF},
title = {New opportunities for managing acute and chronic lung infections.},
journal = {Nature reviews. Microbiology},
volume = {16},
number = {2},
pages = {111-120},
doi = {10.1038/nrmicro.2017.122},
pmid = {29062070},
issn = {1740-1534},
support = {G1000758//Medical Research Council/United Kingdom ; },
abstract = {Lung diseases caused by microbial infections affect hundreds of millions of children and adults throughout the world. In Western populations, the treatment of lung infections is a primary driver of antibiotic resistance. Traditional therapeutic strategies have been based on the premise that the healthy lung is sterile and that infections grow in a pristine environment. As a consequence, rapid advances in our understanding of the composition of the microbiota of the skin and bowel have not yet been matched by studies of the respiratory tree. The recognition that the lungs are as populated with microorganisms as other mucosal surfaces provides the opportunity to reconsider the mechanisms and management of lung infections. Molecular analyses of the lung microbiota are revealing profound adverse responses to widespread antibiotic use, urbanization and globalization. This Opinion article proposes how technologies and concepts flowing from the Human Microbiome Project can transform the diagnosis and treatment of common lung diseases.},
}

RevDate: 2018-11-13

Ma ZS, D Ye (2017)

Trios-promising in silico biomarkers for differentiating the effect of disease on the human microbiome network.

Scientific reports, 7(1):13259 pii:10.1038/s41598-017-12959-3.

Recent advances in the HMP (human microbiome project) research have revealed profound implications of the human microbiome to our health and diseases. We postulated that there should be distinctive features associated with healthy and/or diseased microbiome networks. Following Occam's razor principle, we further hypothesized that triangle motifs or trios, arguably the simplest motif in a complex network of the human microbiome, should be sufficient to detect changes that occurred in the diseased microbiome. Here we test our hypothesis with six HMP datasets that cover five major human microbiome sites (gut, lung, oral, skin, and vaginal). The tests confirm our hypothesis and demonstrate that the trios involving the special nodes (e.g., most abundant OTU or MAO, and most dominant OTU or MDO, etc.) and interactions types (positive vs. negative) can be a powerful tool to differentiate between healthy and diseased microbiome samples. Our findings suggest that 12 kinds of trios (especially, dominantly inhibitive trio with mixed strategy, dominantly inhibitive trio with pure strategy, and fully facilitative strategy) may be utilized as in silico biomarkers for detecting disease-associated changes in the human microbiome, and may play an important role in personalized precision diagnosis of the human microbiome associated diseases.

@article {pmid29038470,
year = {2017},
author = {Ma, ZS and Ye, D},
title = {Trios-promising in silico biomarkers for differentiating the effect of disease on the human microbiome network.},
journal = {Scientific reports},
volume = {7},
number = {1},
pages = {13259},
doi = {10.1038/s41598-017-12959-3},
pmid = {29038470},
issn = {2045-2322},
abstract = {Recent advances in the HMP (human microbiome project) research have revealed profound implications of the human microbiome to our health and diseases. We postulated that there should be distinctive features associated with healthy and/or diseased microbiome networks. Following Occam's razor principle, we further hypothesized that triangle motifs or trios, arguably the simplest motif in a complex network of the human microbiome, should be sufficient to detect changes that occurred in the diseased microbiome. Here we test our hypothesis with six HMP datasets that cover five major human microbiome sites (gut, lung, oral, skin, and vaginal). The tests confirm our hypothesis and demonstrate that the trios involving the special nodes (e.g., most abundant OTU or MAO, and most dominant OTU or MDO, etc.) and interactions types (positive vs. negative) can be a powerful tool to differentiate between healthy and diseased microbiome samples. Our findings suggest that 12 kinds of trios (especially, dominantly inhibitive trio with mixed strategy, dominantly inhibitive trio with pure strategy, and fully facilitative strategy) may be utilized as in silico biomarkers for detecting disease-associated changes in the human microbiome, and may play an important role in personalized precision diagnosis of the human microbiome associated diseases.},
}

Motivation: Widespread interest in the study of the microbiome has resulted in data proliferation and the development of powerful computational tools. However, many scientific researchers lack the time, training, or infrastructure to work with large datasets or to install and use command line tools.

Results: The National Institute of Allergy and Infectious Diseases (NIAID) has created Nephele, a cloud-based microbiome data analysis platform with standardized pipelines and a simple web interface for transforming raw data into biological insights. Nephele integrates common microbiome analysis tools as well as valuable reference datasets like the healthy human subjects cohort of the Human Microbiome Project (HMP). Nephele is built on the Amazon Web Services cloud, which provides centralized and automated storage and compute capacity, thereby reducing the burden on researchers and their institutions.

@article {pmid29028892,
year = {2018},
author = {Weber, N and Liou, D and Dommer, J and MacMenamin, P and Quiñones, M and Misner, I and Oler, AJ and Wan, J and Kim, L and Coakley McCarthy, M and Ezeji, S and Noble, K and Hurt, DE},
title = {Nephele: a cloud platform for simplified, standardized and reproducible microbiome data analysis.},
journal = {Bioinformatics (Oxford, England)},
volume = {34},
number = {8},
pages = {1411-1413},
doi = {10.1093/bioinformatics/btx617},
pmid = {29028892},
issn = {1367-4811},
abstract = {Motivation: Widespread interest in the study of the microbiome has resulted in data proliferation and the development of powerful computational tools. However, many scientific researchers lack the time, training, or infrastructure to work with large datasets or to install and use command line tools.

Results: The National Institute of Allergy and Infectious Diseases (NIAID) has created Nephele, a cloud-based microbiome data analysis platform with standardized pipelines and a simple web interface for transforming raw data into biological insights. Nephele integrates common microbiome analysis tools as well as valuable reference datasets like the healthy human subjects cohort of the Human Microbiome Project (HMP). Nephele is built on the Amazon Web Services cloud, which provides centralized and automated storage and compute capacity, thereby reducing the burden on researchers and their institutions.

In the early 1990's,
Robert Robbins
was a faculty member at Johns
Hopkins, where he directed the informatics core of GDB
— the human gene-mapping database of the international human
genome project. To share papers with colleagues around the world, he
set up a small paper-sharing section on his personal web page. This
small project evolved into The Electronic Scholarly
Publishing Project.

ESP Support

In 1995, Robbins became the VP/IT of the Fred Hutchinson Cancer Research
Center in Seattle, WA. Soon after arriving in Seattle, Robbins secured
funding, through the ELSI component of the US Human Genome Project, to
create the original ESP.ORG web site, with the formal goal of
providing free, world-wide access to the literature of classical genetics.

ESP Rationale

Although the methods of molecular biology can seem almost
magical to the uninitiated, the original
techniques of classical genetics are readily appreciated by one and
all: cross individuals that differ in some inherited trait, collect
all of the progeny, score their attributes, and propose mechanisms
to explain the patterns of inheritance observed.

ESP Goal

In reading the early works of classical genetics, one is drawn, almost
inexorably, into ever more complex models, until molecular explanations
begin to seem both necessary and natural. At that point, the tools
for understanding genome research are at hand. Assisting readers reach
this point was the original goal of The Electronic Scholarly Publishing
Project.

ESP Usage

Usage of the site grew rapidly and has remained high. Faculty began
to use the site for their assigned readings. Other on-line
publishers, ranging from The New York Times to Nature
referenced ESP materials in their own publications. Nobel laureates
(e.g., Joshua Lederberg) regularly used the
site and even wrote to suggest changes and improvements.

ESP Content

When the site began, no journals
were making their early content available in
digital format. As a result, ESP was obliged to digitize classic
literature before it could be made available. For many important
papers — such as
Mendel's original paper
or the
first genetic map
— ESP had to produce entirely new typeset versions of the works,
if they were to be available in a high-quality format.

ESP Help

Early support from the DOE component of the Human Genome Project was
critically important for getting the ESP project on a firm foundation.
Since that funding ended (nearly 20 years ago), the project has been
operated as a purely volunteer effort.
Anyone wishing to assist in these efforts should send an
email to Robbins.